Trase Analysis of deforestation and emissions exposure for slaughterhouse facilities in Brazil

Mapping slaughterhouses supply-shed and exposure to deforestation and emission risk

Trase combines GTA (Animal Transport Guide) movement records, fallback sourcing models where GTA data are not available, and pasture conversion and deforestation data to help companies and financial institutions understand where Brazilian beef facilities are likely sourcing from at-risk areas for deforestation and CO2 emissions exposure, and where production is more likely DCF (Deforestation and Conversion Free).

Open supply shed dashboard Open risk exposure dashboard
Presented data

Driving sustainable decisions based on empirical purchase data.

The dashboards are designed for Consumer Goods Forum-aligned retailers and manufacturers, financial institutions, civil society organisations and sourcing/procurement teams that need asset-level evidence for risk-based due diligence, supplier engagement, support for DCF claims and procurement planning.

Supply shed mapping

Explore facility sourcing municipalities built from the most recent GTA animal movement data available, based on more than 8 million unique GTA records and 62,378 movements, with SIG-SIF and road-distance fallback where GTA coverage is missing. The analysis includes federally inspected slaughterhouses (SIF), the inspection level required for beef export eligibility, and slaughterhouses authorised to operate domestically under state (SIE) or municipal (SIM) inspection. Consortium inspection, where recorded, should be interpreted as a municipal inspection arrangement shared across several municipalities.

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Supply shed risk exposure

Use this dashboard to switch between deforestation and conversion exposure and pasture gross CO2e emissions exposure. Both views classify facility exposure as at-risk or not at-risk and support screening, supplier follow-up requests and DCF evidence review. The deforestation view uses median annual cattle beef deforestation in 2020-2024, while the emissions view applies the same supply-shed structure to pasture gross CO2e emissions from cattle deforestation.

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How the data was prepared

From cattle movements to facility exposure.

The data preparation follows the supply-shed logic used in this paper, which estimates the typical sourcing area of each slaughterhouse facility in Brazil, retains municipality-level flow shares, then links those municipalities to pasture conversion and deforestation indicators. Access methods document here.

1

Map facility sourcing

Facilities are matched to GTA records by CNPJ. GTA movements are expanded to source municipalities and weighted by the share of cattle flow supplying each destination facility.

2

Cover GTA gaps

Where a facility has no GTA match in the most recent available movement data, the fallback combines SIG-SIF state-level slaughter flows with road travel-time filters derived from observed GTA sourcing patterns.

3

Attach source indicators

Municipality-level exposure is based on Trase beef indicators for cattle deforestation, pasture gross CO2e emissions and the corresponding per-tonne intensity values over 2020-2024.

4

Classify exposure

Municipalities are ranked by pasture-conversion exposure or CO2 emission. Those contributing to the first 95% of cumulative exposure are flagged as at-risk; the rest are not at-risk. Facilities with at least 50% of their supply-shed flow from at-risk municipalities are categorised as at-risk.

Exposure index method note

The exposure values shown in the dashboards are network-scaled screening indices. The GTA/SIG-SIF kilograms represent a supply network weight constructed from the most recent GTA data available, indirect movement links and SIG-SIF fallback evidence; they should not be interpreted as annual slaughter volume. For each facility-source municipality pair, the source weight is calculated as that municipality's share of the facility supply shed. Facility-size sensitivity is retained through a supplied volume index based on the facility's total supply-network weight relative to the median facility.

Deforestation Exposure Index = deforestation_per_tonne_m * source_weight_fm * facility_supply_scale_f. Emission Exposure Index uses the same structure with emissions_per_tonne_m. These indicators are designed for comparing relative exposure between source municipalities and facilities, and for prioritising supplier engagement, not for claiming annual attributable hectares or tonnes of CO2e.

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How the dashboards should be used

Evidence for screening, engagement and sourcing decisions.

The dashboards translate broad due-diligence guidance into a practical facility risk screen. Not at-risk exposure can support a lower-risk evidence base for DCF claims, while at-risk exposure should trigger more scrutiny: supplier traceability, source-farm or plot-level evidence, non-compliance checks, grievance review and a mitigation plan before any claim is made. The analysis also considers the role of indirect suppliers in the supply chain, which may represent 79% of deforestation and conversion exposure in Brazil.

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Retailers

Align with forest-positive coalition commodity commitments by checking whether beef facilities are sourcing from not at-risk or at-risk municipalities, prioritising supplier engagement, and steering procurement toward lower-exposure supply sheds.

Financial institutions

Screen clients, holdings and physical assets connected to Brazilian beef, identify where loans or investments may carry deforestation exposure, and focus engagement or covenants on at-risk facilities and sourcing areas. It can also support the Taskforce on Nature-related Financial Disclosures (TNFD), providing a better framework for banks to identify, assess, manage, and disclose nature-related dependencies, impacts, risks, and opportunities.

Civil society organisations

Compare sourcing footprints across facilities and companies, identify where transparency gaps remain, and focus accountability work on the assets and municipalities most associated with deforestation exposure. It provides an essential tool for supporting guidance and voluntary commitments.

Supply chain teams

Use municipality-level flow shares to understand which places shape each facility's exposure profile, then request more granular documentation from at-risk origins.

Source-based view of cattle traceability.

This conceptual network shows how the dashboards translate cattle movement sources into a facility-level screening signal. GTA records document batch movements from an origin to a destination, while supplier follow-up may need CAR/property information to locate farms and verify compliance. Because cattle commonly move through breeding, rearing and finishing stages, the dashboard prioritises facilities whose supply sheds draw heavily from at-risk source municipalities.

Source evidence GTA batch records show animal movements between origins and destinations; CAR/property data is the follow-up layer for locating farms and checking compliance.
Why indirect suppliers matter Direct-only monitoring can miss breeding and rearing farms upstream. Tier 1 indirect suppliers are a practical priority because deeper GTA chains become large and uncertain.
Facility screening signal The dashboard does not claim farm-level traceability. It ranks facilities by the share of their source-municipality flow connected to at-risk deforestation, conversion or emissions exposure.
At-risk source municipality or pathway Prioritisation pathway or mixed origin Observed movement or uncertain link Facility receiving the screened supply shed
Conceptual framing based on GTA batch traceability, CAR/property follow-up and cattle direct/indirect supplier monitoring guidance from GTFI/NWF and Proforest.
Interpretation notes

Transparent signals, not a substitute for traceability.

GTA-based supply sheds reflect observed animal movement patterns where records are available, aggregated at municipality level. SIG-SIF fallback rows are modelled estimates and should be interpreted separately from directly observed GTA sourcing. DCF claims should be supported by facility-level evidence, supplier traceability, and controls appropriate to the exposure class. A facility could still have DCF sourcing in at-risk municipalities if production is traced back to plot level for direct and indirect suppliers.