pith. sign in

arxiv: 2604.13044 · v1 · submitted 2026-03-05 · 💻 cs.CY

Green by Design? Investigating the Energy and Carbon Footprint of Chia Network

Pith reviewed 2026-05-15 15:30 UTC · model grok-4.3

classification 💻 cs.CY
keywords Chia NetworkProof of Space and Timecarbon emissionsblockchain sustainabilityenergy footprintenvironmental impactPoST consensusgreen blockchain
0
0 comments X

The pith

Chia Network produces carbon emissions 18 times higher than claimed due to resource-intensive initialization and ongoing operations.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper investigates the environmental impact of Chia Network, which uses a Proof of Space and Time consensus mechanism and presents itself as a sustainable blockchain alternative. Experimental measurements on a controlled testbed combined with theoretical modeling reveal that creating storage plots and running the network drive annual emissions of 0.88 MtCO2, eighteen times the project's stated figure. This exceeds emissions from other mainstream green blockchains by orders of magnitude. A reader focused on blockchain sustainability would see the work as direct evidence that PoST systems carry hidden hardware and energy costs that undermine their green positioning.

Core claim

Chia Network's Proof of Space and Time consensus leads to carbon emissions of 0.88 MtCO2 per year, eighteen times higher than claimed, when experimental testbed measurements are combined with models of both operational energy use and embodied emissions from hardware.

What carries the argument

Proof of Space and Time (PoST) consensus mechanism, evaluated via Grid'5000 testbed measurements of plot creation and operations plus theoretical models for embodied and operational emissions.

Load-bearing premise

The testbed measurements on Grid'5000 accurately represent the full-scale Chia network and the theoretical models for embodied and operational emissions use representative real-world factors.

What would settle it

Independent, large-scale measurements of energy use across actual Chia farming nodes that produce emissions near the project's claimed low levels would falsify the 18x higher estimate.

Figures

Figures reproduced from arXiv: 2604.13044 by Cl\'ementine Gritti, Rahima Benzenati, Soraya Djerrab.

Figure 1
Figure 1. Figure 1: Chia’s architecture overview • Proof of Space : Farmers pre-compute and store large cryptographic files called plots (108.8 GiB for k=32) on disk. When the network issues a challenge, each farmer’s harvester scans these plots for a valid proof [3]. • Proof of Time : To prevent grinding attacks (rapid, repeated attempts to find proofs), a specialized node called the timelord computes a Verifiable Delay Func… view at source ↗
Figure 2
Figure 2. Figure 2: Comparison of annual CO2 emissions across blockchains (log scale). • Roughly the same as the total annual fossil-fuel CO2 emissions of Lesotho (0.88 Mt), Somalia (0.87 Mt) or Burundi (0.84 Mt) [14]. By contrast, Chia’s own published figure of 0.13 TWh/yr [5] corresponds to only ≈ 0.0499 Mt CO2/yr Thus, our homogeneous scaling (Method 1) produces emissions about 27× higher than Chia’s claim, while our cohor… view at source ↗
read the original abstract

This paper presents a detailed analysis of the environmental impact of Chia Network (Chia for short), a green-claimed blockchain, which uses a Proof of Space and Time (PoST) consensus mechanism. While Chia claims to be a sustainable alternative to Proof-of-Work-based blockchains, our results show that its resource-intensive initialization phase and ongoing operations lead to carbon emissions 18x higher than claimed (0.88 MtCO2/year), exceeding mainstream "green" blockchains by orders of magnitude. We combine experimental measurements from a controlled testbed (Grid'5000) with theoretical modeling of operational and embodied emissions to assess Chia's true sustainability profile.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 2 minor

Summary. The paper analyzes the environmental impact of Chia Network, a blockchain using Proof of Space and Time (PoST). It combines experimental energy measurements from a Grid'5000 testbed with theoretical modeling of operational and embodied emissions to conclude that Chia's carbon footprint is 0.88 MtCO2/year—18 times higher than the network's claims—and exceeds other green blockchains by orders of magnitude.

Significance. If the testbed-to-network scaling is validated with contemporaneous blockchain data, the work would provide valuable empirical grounding for debates on sustainable consensus mechanisms, highlighting potential underestimation of PoST initialization and farming costs. The controlled testbed approach is a methodological strength that could support reproducible comparisons if full data and scaling parameters are released.

major comments (1)
  1. [Methods and Results (scaling/extrapolation subsection)] The central quantitative claim (0.88 MtCO2/year and 18x multiplier) rests on extrapolating Grid'5000 testbed measurements of plotting and farming to the full Chia network. The manuscript must explicitly state (a) the total plot count or storage capacity assumed for the global network, (b) the exact scaling multiplier applied to the testbed runs, and (c) whether these parameters come from contemporaneous netspace statistics or internal modeling. This scaling step is load-bearing; modest errors in assumed scale or hardware mix would directly affect the headline result.
minor comments (2)
  1. [Theoretical modeling section] Clarify the exact electricity carbon intensity factors and drive embodied-emission coefficients used in the theoretical model, including their sources and sensitivity ranges, to allow readers to assess robustness.
  2. [Abstract] The abstract states the result exceeds 'mainstream green blockchains by orders of magnitude' without naming the comparators or providing the quantitative deltas; move this comparison to a dedicated table or figure in the main text.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful and constructive review of our manuscript. The single major comment identifies a need for greater explicitness in our scaling methodology, which we accept and will address through revision.

read point-by-point responses
  1. Referee: [Methods and Results (scaling/extrapolation subsection)] The central quantitative claim (0.88 MtCO2/year and 18x multiplier) rests on extrapolating Grid'5000 testbed measurements of plotting and farming to the full Chia network. The manuscript must explicitly state (a) the total plot count or storage capacity assumed for the global network, (b) the exact scaling multiplier applied to the testbed runs, and (c) whether these parameters come from contemporaneous netspace statistics or internal modeling. This scaling step is load-bearing; modest errors in assumed scale or hardware mix would directly affect the headline result.

    Authors: We agree that these parameters should be stated explicitly to support reproducibility and verification. In the revised manuscript we will expand the Methods section with a dedicated paragraph that reports (a) the total netspace/storage capacity assumed for the global network, (b) the precise scaling multiplier applied to the Grid'5000 measurements, and (c) that both values are taken directly from contemporaneous public netspace statistics published by Chia blockchain explorers at the time of the experiments (with exact dates and sources provided). We will also deposit the raw scaling parameters and data sources as supplementary material. These additions will not alter the quantitative results but will make the extrapolation fully transparent and auditable. revision: yes

Circularity Check

0 steps flagged

No significant circularity: independent testbed data and standard factors

full rationale

The paper's central claims rest on direct experimental measurements of energy use during plotting and farming phases collected from the Grid'5000 testbed, combined with standard emission-factor tables and embodied-carbon models drawn from external literature. No load-bearing equation reduces a derived quantity to a fitted parameter by construction, no prediction is obtained by renaming or re-using an input fit, and no uniqueness or ansatz is imported via self-citation. Scaling assumptions for total network size are stated as external inputs (blockchain netspace statistics) rather than solved from the paper's own results. The derivation chain therefore remains self-contained against independent benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim depends on the representativeness of Grid'5000 testbed runs for the global network and on standard but unstated emission factors for electricity and hardware manufacturing.

axioms (2)
  • domain assumption Testbed measurements scale linearly to the full Chia network size and hardware mix
    Invoked when extrapolating from controlled experiments to annual global emissions
  • domain assumption Standard emission factors for embodied carbon and electricity accurately reflect Chia's operational conditions
    Used in the theoretical modeling component

pith-pipeline@v0.9.0 · 5412 in / 1240 out tokens · 61728 ms · 2026-05-15T15:30:27.680970+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

36 extracted references · 36 canonical work pages

  1. [1]

    Carbon intensity.https://ember-energy.org/app/uploads/2025/03/ US-Electricity-2025-Special-Report.pdf

  2. [2]

    Ccri carbon sustainability metrics.https://indices.carbon-ratings. com/

  3. [3]

    Chia green paper.https://docs.chia.net/green-paper-abstract/

  4. [4]

    Chia (xch) netspace chart.https://spacescan.io/charts/netspace

  5. [5]

    Chiapower model.https://chiapower.org/

  6. [6]

    Chia’s documentation.https://docs.chia.net/

  7. [7]

    Compressed netspace estimate.https://xch.farm/compressed- netspace/

  8. [8]

    Computer usage and national energy consumption: Results from a field- metering study.https://eta-publications.lbl.gov/sites/default/ files/computers_lbnl_report_v4.pdf

  9. [9]

    Datalayer secured by chia’s public blockchain.https://ggim.un.org/ meetings/2022/4th-EG-LAM/documents/4.4_Neil_Cohen.pdf

  10. [10]

    https://www.epa.gov/greenvehicles/greenhouse-gas-emissions- typical-passenger-vehicle

    Greenhouse gas emissions from a typical passenger vehicle. https://www.epa.gov/greenvehicles/greenhouse-gas-emissions- typical-passenger-vehicle

  11. [11]

    I/o statistics fields.https://www.kernel.org/doc/Documentation/ iostats.txt

  12. [12]

    Laptop.https://en.wikipedia.org/wiki/Laptop

  13. [13]

    https://journal.uptimeinstitute.com/large-data-centers-are- mostly-more-efficient-analysis-confirms/

    Large data centers are mostly more efficient, analysis confirms. https://journal.uptimeinstitute.com/large-data-centers-are- mostly-more-efficient-analysis-confirms/

  14. [14]

    org/wiki/List_of_countries_by_carbon_dioxide_emissions

    List of countries by carbon dioxide emissions.https://en.wikipedia. org/wiki/List_of_countries_by_carbon_dioxide_emissions

  15. [15]

    Monitoring using kwollect.https://www.grid5000.fr/w/Monitoring_ Using_Kwollect

  16. [16]

    pcf lca whitepaper.https://www.delltechnologies.com/asset/zh- hk/products/multi-product/industry-market/pcf-lca-whitepaper. pdf. 16

  17. [17]

    Samsung mz7km480hmhq-00005 sm863a 480gb sata 6gbps 2.5inch ssd.https://www.serversupply.com/SSD/SATA-6GBPS/480GB/SAMSUNG/ MZ7KM480HMHQ-00005_293583.htm

  18. [18]

    Sustainability in blockchain: A systematic literature review on scalability and power consumption issues.Energies, 16(3), 2023

    Hani Alshahrani, Noman Islam, Darakhshan Syed, Adel Sulaiman, Mana Saleh Al Reshan, Khairan Rajab, Asadullah Shaikh, Jaweed Shuja- Uddin, and Aadar Soomro. Sustainability in blockchain: A systematic literature review on scalability and power consumption issues.Energies, 16(3), 2023

  19. [19]

    Green blockchain – a move to- wards sustainability.Journal of Cleaner Production, 430:139541, 2023

    Yehia Ibrahim Alzoubi and Alok Mishra. Green blockchain – a move to- wards sustainability.Journal of Cleaner Production, 430:139541, 2023

  20. [20]

    Verifiable de- lay functions

    Dan Boneh, Joseph Bonneau, Benedikt B¨ unz, and Ben Fisch. Verifiable de- lay functions. InAnnual international cryptology conference - CRYPTO’18, pages 757–788. Springer, 2018

  21. [21]

    Bitcoin energy consumption index.https://digiconomist

    Alex de Vries. Bitcoin energy consumption index.https://digiconomist. net/bitcoin-energy-consumption, 2024

  22. [22]

    The european green deal.https://commission.europa.eu/ strategy-and-policy/priorities-2019-2024/european-green- deal_en, 2019

    EU. The european green deal.https://commission.europa.eu/ strategy-and-policy/priorities-2019-2024/european-green- deal_en, 2019

  23. [23]

    Environmental and economic assessment of desktop vs

    Miguel Ferreira, Idalina Domingos, Lenise Santos, Anna Barreto, and Jos´ e Ferreira. Environmental and economic assessment of desktop vs. laptop computers: A life cycle approach.Sustainability, 17(10), 2025

  24. [24]

    Cambridge bitcoin electricity consumption index.https://ccaf.io/cbnsi/cbeci/ghg/comparisons, 2025

    Cambridge Centre for Alternative Finance. Cambridge bitcoin electricity consumption index.https://ccaf.io/cbnsi/cbeci/ghg/comparisons, 2025

  25. [25]

    Energy consump- tion of cryptocurrencies beyond bitcoin.Joule, 4(9):1843–1846, 2020

    Ulrich Gallersd¨ orfer, Lena Klaaßen, and Christian Stoll. Energy consump- tion of cryptocurrencies beyond bitcoin.Joule, 4(9):1843–1846, 2020

  26. [26]

    Lee, David Brooks, and Carole-Jean Wu

    Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, and Carole-Jean Wu. Act: designing sustainable com- puter systems with an architectural carbon modeling tool. InInternational Symposium on Computer Architecture - ISCA’22, page 784–799, 2022

  27. [27]

    The energy consumption of proof- of-stake systems: Replication and expansion

    Juan Ignacio Iba˜ nez and Francisco Rua. The energy consumption of proof- of-stake systems: Replication and expansion. arXiv 2302.00627, 2023

  28. [28]

    Jones, and Peipei Zhou

    Shixin Ji, Zhuoping Yang, Xingzhen Chen, Stephen Cahoon, Jingtong Hu, Yiyu Shi, Alex K. Jones, and Peipei Zhou. Scarif: Towards carbon modeling of cloud servers with accelerators, 2024

  29. [29]

    An analysis of energy consumption and carbon footprints of cryptocurrencies and possible solutions.Digital Com- munications and Networks, 9(1):79–89, 2023

    Varun Kohli, Sombuddha Chakravarty, Vinay Chamola, Kuldip Singh Sangwan, and Sherali Zeadally. An analysis of energy consumption and carbon footprints of cryptocurrencies and possible solutions.Digital Com- munications and Networks, 9(1):79–89, 2023

  30. [30]

    Quantification of energy and carbon costs for mining cryptocurrencies.Nature Sustainability, 1, 2018

    Max Krause and Thabet Tolaymat. Quantification of energy and carbon costs for mining cryptocurrencies.Nature Sustainability, 1, 2018. 17

  31. [31]

    Best practices for ana- lyzing the direct energy use of blockchain technology systems: Review and policy recommendations.Energy Policy, 156, 2021

    Nuoa Lei, Eric Masanet, and Jonathan Koomey. Best practices for ana- lyzing the direct energy use of blockchain technology systems: Review and policy recommendations.Energy Policy, 156, 2021

  32. [32]

    Carbon emission modeling for high- performance computing-based ai in new power systems with large-scale renewable energy integration.Processes, 13(2), 2025

    Haoyang Liu and Jiangtao Zhai. Carbon emission modeling for high- performance computing-based ai in new power systems with large-scale renewable energy integration.Processes, 13(2), 2025

  33. [33]

    Bitcoin: A peer-to-peer electronic cash system

    Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system. 2009

  34. [34]

    Chia’s website.https://www.chia.net/

    Chia Network. Chia’s website.https://www.chia.net/

  35. [35]

    Promoting rigor in blockchain energy and environmental footprint research: A systematic literature re- view.Blockchain: Research and Applications, 5(1), 2024

    Ashish Rajendra Sai and Harald Vranken. Promoting rigor in blockchain energy and environmental footprint research: A systematic literature re- view.Blockchain: Research and Applications, 5(1), 2024

  36. [36]

    Swamit Tannu and Prashant J. Nair. The dirty secret of ssds: Embodied carbon.ACM SIGEnergy Energy Informatics Review, 3:4–9, 2023. 18