Carbon
Footprint
Pawston Cat Foods Ltd
Your full greenhouse gas inventory broken down by category, scope, and time period. Charts update as new records are processed.
tCO₂e, with each category's share of the total
| Category | Scope | Spend | tCO₂e | % of Total | GSD |
|---|---|---|---|---|---|
| Cat 1 Purchased goods & services, dairy | Scope 3 | £2,040,000 | 2.2k | 15.9% | 1.43 |
| Cat 1 Purchased goods & services, meat & poultry | Scope 3 | £2,320,000 | 2.0k | 14.8% | 1.45 |
| Purchased grid electricity | Scope 2 | £540,000 | 1.8k | 13.4% | 1.12 |
| Cat 1 Purchased goods & services, fruit & vegetables | Scope 3 | £626,600 | 1.7k | 12.1% | 1.39 |
| Cat 4 Upstream transport & distribution | Scope 3 | £1,350,000 | 1.4k | 10.4% | 1.49 |
| Cat 1 Purchased goods & services, packaging | Scope 3 | £1,487,700 | 1.2k | 8.6% | 1.51 |
| Cat 3 Fuel- and energy-related activities | Scope 3 | £0 | 841.0 | 6.1% | 1.20 |
| Natural gas stationary combustion | Scope 1 | £165,000 | 760.0 | 5.6% | 1.15 |
| Cat 1 Purchased goods & services, specialty pet nutrition | Scope 3 | £522,900 | 600.0 | 4.4% | 1.55 |
| Cat 7 Employee commuting | Scope 3 | £0 | 493.0 | 3.6% | 1.67 |
| Company-vehicle fleet mobile combustion | Scope 1 | £140,000 | 450.0 | 3.3% | 1.18 |
| Cat 5 Waste generated in operations | Scope 3 | £180,000 | 240.0 | 1.8% | 1.58 |
| Cat 6 Business travel (rail) | Scope 3 | £95,000 | 14.0 | 0.1% | 1.33 |
How your emissions flow from boundary to scope to category to source.
Emissions attributed to your sites this period. Intensity uses each site's recorded headcount.
| Site | tCO₂e | % of site-attributed | tCO₂e per employee |
|---|---|---|---|
| Wolverhampton production | 10.7k | 83.2% | 51 |
| Porto distribution | 1.4k | 11.0% | 31 |
| London head office | 540.0 | 4.2% | 14 |
| Cambridge R&D lab | 210.0 | 1.6% | 8.8 |
Not attributed to a site: 806.0 tCO₂e of 13.7k tCO₂e recorded this period.
Trends, anomalies, and year-on-year movement in your inventory, with narrative insights written by your Hemera analyst.
Your emissions plotted against a 1.5°C-aligned pathway (4.2% of the base year each year, on a straight line). The gap between the line and the path is the reduction still to find. Business-as-usualshows where you'd land taking no further action.
Reduction commitments locked against the FY2024-25 baseline. Progress tracks each new inventory against the science-based pathway.
Net change: -8.3% (-1,240 tCO₂e)
Where each emission source sits on a map of size (how big it is) versus uncertainty (how confident we are). Top-right needs work first.
The same sources, ranked. Switch the threshold to see which sources stay in scope under stricter materiality rules.
- 01Purchased goods, dairy & meatScope 330.7%30.7%1.43Fine for now
- 02Purchased goods, fruit & vegetablesScope 312.1%42.8%1.39Fine for now
- 03Upstream transport & distributionScope 310.4%53.2%1.49Fine for now
- 04Purchased goods, packagingScope 38.6%61.8%1.51Replace with meter or fuel readings
- 05Fuel- and energy-related activitiesScope 36.1%67.9%1.20Good as it is, keep it up to date
- 06Business travel & employee commutingScope 33.7%71.6%1.55Fine for now
Written by your Hemera analyst.
Your value chain accounts for 77.7% of total emissions. Purchased goods (dairy & meat) and upstream transport are the two largest categories.
Switching the delivery fleet to EVs could cut Scope 1 by ~70% (≈ 843 tCO₂e). Payback period estimated at 30 months given current diesel costs.
Total emissions fell 8.3% vs FY2023-24 baseline, driven by the Reading green tariff switch and route consolidation.
Commuting estimates use DEFRA averages. A staff travel survey would narrow the range, and the figure itself can move up or down.
Pedigree scoring across your inventory: geographic distance, temporal correlation, and data representativeness.
How many raw transactions were admitted into the published inventory, and why the rest were excluded.
Good. A solid mix of measured and estimated data. More supplier-specific figures would lift this to A.
The band is how precisely we can state your total. It narrows as real data replaces assumptions, and it can widen when new coverage is added. The line is the best estimate; it can move up or down.
How much to trust this
We are most confident about the comparisons: what your biggest source is, which data upgrade helps most, whether a change is big enough to show. The exact width of the range is our best estimate, built conservatively, and it sharpens as real data replaces assumptions.
- Comparisons and rankings. Which category is your biggest, which data upgrade narrows your range most, whether a claimed reduction is big enough to show. These hold even if our uncertainty estimates are somewhat off, because an error moves everything together.
- Directions. Better data narrows the range. That is arithmetic, not opinion.
- The exact width. It is built from published research and deliberately conservative assumptions. We have not yet had enough measured real-world data to test the width against reality. As customers replace estimates with meter readings and supplier figures, we score our ranges against what the real data shows, and we will publish what we find either way.
Your Hemera analyst attaches supporting documents, invoices, utility bills and certificates, to individual activity records as they prepare your inventory. Evidence ships with your audit pack, so a reviewer can trace any figure back to its source document.
The highest-impact things you can do to tighten your footprint, ranked by how much of the range around your total each one removes. Payoffs are measured on your own data, from the same confidence interval shown on your footprint.
Action 1: Replace the meat and poultry spend estimate with supplier data
Medium effortTamarside Meats is your second-largest source and is still priced from a Defra EEIO 2022 spend factor. A product-level footprint from Tamarside would swap the spend estimate for measured data.
Could cut your total uncertainty by ~15.8%£2,320,000 affectedAction 2: Run an employee commuting survey
Low effortCommuting is modelled from DEFRA national averages. A staff travel survey replaces the estimate with measured mode and distance, and usually lowers the figure too.
Could cut your total uncertainty by ~7.4%Action 3: Load packaging weights from Greenridge
Low effortPackaging is priced from invoice value, not material weight. A Greenridge weight log, once supplied, would move this line onto activity data.
Could cut your total uncertainty by ~6.1%£1,487,700 affectedAction 4: Replace the HGV average with Frostline fuel data
Medium effortUpstream transport is priced from Frostline's route data (tonne-km) with the DEFRA 2024 v1.1 HGV average laden factor. Frostline's fuel export would replace the average with measured fuel use.
This area drives ~6.2% of your total uncertainty£1,350,000 affectedWe cannot yet put a figure on where this action lands, so this shows the most it could remove: the share of the range these rows drive.
UK-headquartered cat-food brand consolidating four legal entities under an operational-control boundary. Children roll up deterministically from their underlying records; each retains its own audit trail and methodology pin.
| Entity | Scope 1 | Scope 2 | Scope 3 | Total | Records |
|---|---|---|---|---|---|
| Pawston Cat Foods Ltd | 40 | 180 | 421 | 641 | 28 |
| Pawston Cat Foods Manufacturing Ltd | 1,080 | 1,420 | 8,589 | 11,089 | 150 |
| Pawston Iberia Lda | 75 | 200 | 1,556 | 1,831 | 44 |
| Pawston Pet Innovations Ltd | 15 | 40 | 72 | 127 | 12 |
Footprint ledger
Every change to your inventory, logged with a cryptographic hash of the previous event and exportable for audit.