Category 7 Starter Kit: Employee Commuting

Calculate emissions from employee commuting using practical survey or modeled methods, then reduce emissions with programs that actually change behavior.

Scope 3, Made PracticalStarter KitStarter Kit90 min setup

Disclaimer: Educational only. Respect privacy and data handling requirements. Use factors and methods consistent with your reporting standard.

What you'll accomplish

By implementing this starter kit, you will:

Understand what Scope 3 Category 7 (Employee Commuting) includes
Choose a calculation method you can run today (survey, modeled, or proxy)
Build a minimum viable commuting dataset
Estimate emissions and document assumptions clearly
Identify reduction programs that are realistic and measurable

Who this is for

•Sustainability owners building Scope 3
•People Ops / HR teams who can run surveys
•Facilities teams managing workplace programs (parking, shuttles, bike facilities)
•Finance teams supporting commuter benefits

What Category 7 means (plain English)

Employee commuting = travel between home and work for employees.

Commonly included:

• personal vehicle commuting
• public transit
• carpool
• walking/biking (usually zero direct emissions)
• remote/hybrid work impacts (fewer commute days)

Not Category 7:

• business travel (Category 6)
• freight and delivery
• customer travel (depends on boundary; document your choice)

Quick start (90 minutes)

Choose your boundary (which employees and which sites)

Pick a method: Survey (recommended) or Modeled (acceptable) or Proxy (first pass)

Run the commuter survey template (Template A) OR set up a modeled approach (Template B)

Convert results into annual commute miles/km by mode

Apply emission factors and calculate emissions

Document assumptions and limitations (Template E)

Boundary checklist

Document:

• Included population: full-time only? part-time? contractors?
• Included sites: all offices or selected
• Reporting year
• Remote/hybrid: how you treat remote days
• Work from home energy: commonly excluded from Cat 7; if included, document separately

Methods (choose one for v1)

Tier 0 — Proxy (fastest)

Use a high-level proxy approach if you have no data:

• employee count × average commute distance × assumed mode split
• Use standard assumptions and document heavily

Tier 1 — Modeled (good)

Use employee home ZIP/postal code (or regional centroid) to estimate distance to worksite.

• Requires privacy-safe handling
• Requires mode split assumptions unless you have benefits data

Tier 2 — Survey-based (best for most teams)

Ask employees commute mode, distance/time, and commute days per week.

• Highest practical accuracy for most organizations
• Creates reduction program insight (what people would change)

Beginner rule: a good survey beats a fake "precise" model built on bad assumptions.

Step-by-step implementation

1Decide: survey or modeled

If you can run a survey: do it.
If you can't: start modeled + plan a survey next cycle.

2Collect the minimum data

Minimum fields you need:

• number of commuting days per week (or per month)
• commute distance (one-way or round-trip, but be consistent)
• commute mode (car, transit, rail, bike, walk, etc.)
• occupancy for carpool (optional but helpful)
• remote days per week (if hybrid)

3Convert to annual distance by mode

Basic logic:

If you don't know exact workdays, use a reasonable standard and document it.

4Calculate emissions

General formula:

Activity examples:

• car miles × EF
• transit passenger-miles × EF
• rail passenger-miles × EF

Walking/biking: typically zero direct emissions.

5QA checks (minimum viable)

Check:

• impossible distances (e.g., 400 miles one-way daily)
• mode shares that look unrealistic for your geography (flag, don't assume wrong)
• missing responses (document response rate)
• consistency across sites/regions

Reduction programs (what actually moves the needle)

Use the Avoid / Shift / Improve framework:

Avoid

• remote/hybrid policies (where feasible)
• flexible schedules to reduce peak traffic (indirect effect)

Shift

• transit subsidies and pre-tax benefits
• shuttle programs for transit hubs
• carpool matching + preferential parking

Improve

• EV commuter incentives (charging access, preferred rates)
• bike facilities (secure storage, showers)
• parking pricing reform (powerful but sensitive)

Governance

Set a commuting program goal and measure uptake

Templates (copy/paste)

Template A — Employee Commuting Survey (beginner-friendly)

Employee Commuting Survey (Category 7)

1) Primary worksite (office/location):
2) How many days per week do you typically commute to the worksite?
   - 0 / 1 / 2 / 3 / 4 / 5
3) On days you commute, what is your primary commute mode?
   - Drive alone
   - Carpool
   - Bus
   - Train/Subway/Light rail
   - Bike
   - Walk
   - Other: ______
4) Approximately how far is your one-way commute?
   - [ ] miles   [ ] km   Distance: _____
5) If you carpool, how many people are typically in the car (including you)?
   - 2 / 3 / 4 / 5+
6) If your mode varies, what is your approximate split? (optional)
   - % drive / % transit / % rail / % other
7) Optional: What would most help you reduce car commuting?
   - Better transit access
   - Subsidy/benefits
   - Flexible schedule
   - EV charging
   - Carpool support
   - Bike facilities
   - Other: ______

Template B — Modeled Method Inputs (privacy-safe)

Worksite	Employee count	Avg one-way distance (modeled)	Commute days/week	Mode split assumption	Notes
—	—	—	—	—	—

Template C — Commuting Dataset Table (starter)

Period	Worksite	Mode	Employees	Avg round-trip distance	Unit	Commute days/year	Annual distance	EF used	Emissions (kgCO2e)	Notes
—	—	—	—	—	—	—	—	—	—	—

Template D — QA and Response Log

Date	Issue	Severity	Decision	Owner	Notes
—	—	—	—	—	—

Template E — Method and Limitations Note

Category 7 (Employee Commuting) Method Note

Boundary:
- Included population:
- Included worksites:
- Reporting year:
- Remote/hybrid treatment:

Method:
- Tier used (Proxy / Modeled / Survey)
- Key assumptions:
  - Commute days/year:
  - Mode split basis:
  - Distance basis:

Data quality:
- Survey response rate (if survey used):
- Known gaps:

Known limitations:
- [example: low response rate at one site]
- [example: distance estimates based on ZIP centroids]

Common pitfalls

•Mixing business travel into commuting (Category 6 vs 7 confusion)
•Not accounting for remote days (overstates commuting)
•Collecting overly sensitive data without a privacy plan
•Treating a low-response survey as "truth" without documenting limitations

KPIs to track

•Survey response rate (if survey method)
•Mode split (drive alone %, transit %, etc.)
•Estimated emissions trend (year-over-year)
•Program uptake: transit benefits enrollment, carpool participation, EV charging users
•"Drive alone share" trend (often the key target)

Change log

v1.0 (2026-01): Latest release