← Cockpit
INF_014predictionEnergyDC-carbon-emissions

Data-center industry could emit up to 2.5 billion tons of CO2 cumulatively through 2030 if powered primarily by fossil fuels — a scale that materially delays global climate-pledge compliance.

Predictor: Morgan Stanley

Prior probability
50.0%
Current probability
42.0%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-01-01 – 2026-10-31
Edges in / out
4 / 0
Tickers exposed
30

Prediction text

Data-center industry could emit up to 2.5 billion tons of CO2 cumulatively through 2030 if powered primarily by fossil fuels — a scale that materially delays global climate-pledge compliance. | Annual hyperscaler sustainability reports

Key catalyst: Annual hyperscaler sustainability reports

Watch events: IEA 'Electricity' annual report; hyperscaler Scope-2 emissions disclosures; nuclear restart pace

Resolution evidence

Status: pending

IEA DC emissions trajectory shows DC-sector CO2 roughly tripling 2024-2030 in a gas-heavy scenario.

Predictor: Morgan Stanley

κ + Brier as of 2026-05-22
κ (discount)
0.633
Brier
0.0442
excellent
Hits / Misses
1 / 0
of 2 resolved
Hit rate
50.0%
Calibration plot (stated vs observed)

Evidence about this node from Morgan Stanley is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

4 prob_history rows
0%25%50%75%100%prior 50%2026-05-022026-05-172026-05-24
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 42.0%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 1 fired ✓ · 2 overdue ⏱ · 2 pending
  1. 2024-09-03hitMorgan Stanley research publishes 2.5B tons CO2 cumulative emissions through 2030 thesis
    How: Morgan Stanley publishes formal research report estimating 2.5B tons cumulative CO2 from data centers through 2030 if powered by fossil fuels
    Source: Reuters via U.S. News — Global Data Center Industry to Emit 2.5 Billion Tons of CO2 Through 2030conf 99%
    Notes: HIT (basis claim) — Morgan Stanley research published September 2024 with the 2.5B tons figure verbatim.
  2. 2026-03-05overdueQ1 window check-in (25%)
  3. 2026-05-07overdueQ2 window check-in (50%)
  4. 2026-04-01 → 2026-09-30pendingHyperscaler 2026 sustainability reports show emissions trajectory off-target
    How: ≥3 of (Google, Microsoft, Meta, Amazon) publish 2025 sustainability reports showing total emissions exceeding their 2030 net-zero pathway baseline
    Source: Bisnow — Morgan Stanley: Data Center Carbon Emissions To Triple By 2030conf 85%
  5. 2026-07-09pendingQ3 window check-in (75%)
  6. 2026-06-01 → 2027-12-31pendingMajor hyperscaler walks back 2030 net-zero pledge or extends timeline
    How: At least one Tier-1 hyperscaler (GOOG, MSFT, META, AMZN) publicly extends, weakens, or delays 2030 net-zero/carbon-neutral commitment
    Source: DCD — Morgan Stanley: Data center industry will emit 2.5bn tons of CO2 by 2030conf 70%
    Notes: Microsoft already disclosed 30% increase in emissions vs 2020 baseline in 2024 reporting.
  7. 2026-06-01 → 2028-12-31pendingCarbon removal market scales 5x to meet data-center decarbonization demand
    How: Direct air capture / engineered carbon removal market reaches ≥5x 2024 capacity by 2028 driven by data-center demand
    Source: Latitude Media — Will the data center boom boost carbon removal?conf 60%
  8. 2026-11-01 → 2028-12-31pendingClimate policy compliance gap formally documented in COP/IPCC outputs
    How: COP31/COP32 or IPCC technical paper formally cites data-center sector as material drag on country net-zero commitments
    Source: ESG News — Data Centers to Emit 2.5B Tons of CO2 by 2030, Driving Demand for Decarbonizationconf 55%
  9. 2027-01-01 → 2030-12-31pendingAnnual data-center GHG emissions rise to ~600 Mt CO2-equiv by 2030 (3x 2024)
    How: Annual data-center GHG emissions tracked at ≥500 Mt CO2-eq by 2030 vs ~200 Mt baseline in 2024
    Source: Carbon Herald — AI Data Centers To Become Major Emitters By 2030conf 75%

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 42%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-24T02:00:02Z42.0%+1.2pp
Network propagation: 40.8% → 42.0%
4-iter LBP, residual 0.01000 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 806b02f8
LBP2026-05-17T02:00:01Z40.8%+2.4pp
Network propagation: 38.4% → 40.8%
5-iter LBP, residual 0.00689 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e607fa96
metadata_milestone_miss_sweep2026-05-15T22:14:51Z38.4%-5.7pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.384 blend=0.384 LLR=-0.237 κ=0.58 no_blend
Raw metadata
{
  "trf": 0.5546964117761428,
  "kappa": 0.5833,
  "base_rate": null,
  "predictor": "Morgan Stanley",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.23650779755949214,
  "bayes_factor": "1.3:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.4411471277520515,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "quartile_checkpoint",
      "kappa": 0.5833,
      "label": "Q2 window check-in (50%)",
      "weight": 0.05,
      "strength": "weak",
      "confidence": null,
      "source_url": null,
      "adjusted_llr": -0.2365077975594923,
      "expected_date": "2026-05-07",
      "measurement_criterion": null
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.6117125117566999,
  "outside_weight": 0.38828748824330006,
  "posterior_prob": 0.38390274149128145,
  "posterior_logit": -0.47301559511898444,
  "predictor_brier": 0.01,
  "inside_posterior": 0.38390274149128145,
  "blended_posterior": 0.38390274149128145,
  "reference_class_id": null,
  "total_adjusted_llr": -0.2365077975594923,
  "predictor_n_resolved": 1
}
metadata_milestone_miss_sweep2026-05-02T22:07:21Z44.1%-5.9pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.441 blend=0.441 LLR=-0.237 κ=0.58 no_blend
Raw metadata
{
  "trf": 0.5976179033649615,
  "kappa": 0.5833,
  "base_rate": null,
  "predictor": "Morgan Stanley",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": 0,
  "bayes_factor": "1.3:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.5,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "quartile_checkpoint",
      "kappa": 0.5833,
      "label": "Q1 window check-in (25%)",
      "weight": 0.05,
      "strength": "weak",
      "confidence": null,
      "source_url": null,
      "adjusted_llr": -0.2365077975594923,
      "expected_date": "2026-03-05",
      "measurement_criterion": null
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "prior_prob",
  "inside_weight": 0.5816674676445269,
  "outside_weight": 0.4183325323554731,
  "posterior_prob": 0.4411471277520515,
  "posterior_logit": -0.2365077975594923,
  "predictor_brier": 0.01,
  "inside_posterior": 0.4411471277520515,
  "blended_posterior": 0.4411471277520515,
  "reference_class_id": null,
  "total_adjusted_llr": -0.2365077975594923,
  "predictor_n_resolved": 1
}

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

No propagation data yet. Run inference/.venv/bin/python scripts/ops/run_loopy_belief_propagation.py on the droplet, or wait for the Sunday 02:00 UTC weekly cron.

Ticker exposure

30 ticker(s) linked

Beneficiaries (21)

CRWVFLNCEQIXAPLDWULFARGANNBISIRENFSLRAAPLAMTAMZNETNGOOGLHUBBIRMMETAMSFTORCLSFTBYSTX

Adverse (3)

BTUCEIXARCH

Prerequisites (4)

Predictions that must hit first
TypePredTitleDomainLag
correlateS_COMPUTE_1GW_2027Compute: 1GW operational by Jun 2027compute_scale
correlateS_GRID_50GW_202750GW dedicated AI/data center grid by Dec 2027energy_grid_expansion
correlateS_COMPUTE_10GW_2028Compute: 10GW total by Dec 2028compute_scale
correlateS_COMPUTE_100GW_2030Compute: 100GW national-scale by Dec 2030compute_scale

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": true,
  "qty": "up to 2.5B tons CO2",
  "mode": "FORECAST",
  "role": "Cited-Firm",
  "context": "Morgan Stanley 2026 sustainability outlook quantifies the carbon externality of the AI infrastructure buildout, providing the data-anchor behind Eric Schmidt's 'steel mills' framing.",
  "to_year": 2030,
  "conv_cues": "specific tonnage; explicit ceiling",
  "direction": "NUMERIC_TARGET",
  "from_year": 2026,
  "timeframe": "cumulative through 2030",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Morgan Stanley research publishes 2.5B tons CO2 cumulative emissions through 2030 thesis",
      "notes": "HIT (basis claim) — Morgan Stanley research published September 2024 with the 2.5B tons figure verbatim.",
      "source": "Reuters via U.S. News — Global Data Center Industry to Emit 2.5 Billion Tons of CO2 Through 2030",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.99,
      "source_url": "https://www.usnews.com/news/technology/articles/2024-09-03/global-data-center-industry-to-emit-2-5-billion-tons-of-co2-through-2030-morgan-stanley-says",
      "expected_date": "2024-09-03",
      "observed_date": "2024-09-03",
      "research_origin": "deep_research",
      "measurement_criterion": "Morgan Stanley publishes formal research report estimating 2.5B tons cumulative CO2 from data centers through 2030 if powered by fossil fuels"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -4,
      "source_id": null,
      "expected_date": "2026-03-05",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2026-05-07",
      "observed_date": null,
      "miss_emitted_at": "2026-05-15T22:14:51.696830+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "llm_pre_event",
      "label": "Hyperscaler 2026 sustainability reports show emissions trajectory off-target",
      "source": "Bisnow — Morgan Stanley: Data Center Carbon Emissions To Triple By 2030",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.85,
      "source_url": "https://www.bisnow.com/national/news/data-center/morgan-stanley-data-center-carbon-emissions-will-triple-by-2030-thanks-to-ai-125822",
      "expected_date": "2026-07-01",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-09-30",
        "from": "2026-04-01"
      },
      "measurement_criterion": "≥3 of (Google, Microsoft, Meta, Amazon) publish 2025 sustainability reports showing total emissions exceeding their 2030 net-zero pathway baseline"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -1,
      "source_id": null,
      "expected_date": "2026-07-09",
      "observed_date": null
    },
    {
      "kind": "event",
      "label": "Data-center industry could emit up to 2.5 billion tons of CO2 cumulatively through 2030 if powered primarily by fossil fuels — a scale that ",
      "status": "pending",
      "weight": 1,
      "ordinal": 0,
      "source_id": "INF_014",
      "expected_date": "2026-09-10",
      "observed_date": null
    },
    {
      "kind": "llm_post_event",
      "label": "Major hyperscaler walks back 2030 net-zero pledge or extends timeline",
      "notes": "Microsoft already disclosed 30% increase in emissions vs 2020 baseline in 2024 reporting.",
      "source": "DCD — Morgan Stanley: Data center industry will emit 2.5bn tons of C
... (truncated)