The Unreasonable Ecological Cost of #CryptoArt (Part 2)

This is Part 2 of a N-part series, accompanying the website http://cryptoart.wtf

Part 0 (26th Feb): A short summary of the main article has been published in the online publication Flash Art under the title “Toward a New Ecology of Crypto Art: A Hybrid Manifesto”. I suggest this as a starting point.

Part 1: I present my motivations, findings, and my conclusions as a result of these findings.

Part 2 (this article): I present the underlying data and methodology that gave rise to these findings, along with more statistics. It’s more aimed at those who wish to dig deeper into the numbers, and/or technically interrogate my claims.

Part 3 (25th Feb): I — with contributions from many others — have put together some information with regards to more sustainable NFTs.

[Data: Sources | NFTs (anonymized)| Artists (anonymized)]

Additional notes

There is a common fallacy along the lines of “The same energy will be consumed whether a block is empty or contains your transaction, thus a transaction has no impact on the energy consumption of a block being mined, or on the environment”. This is based on a gross misunderstanding of what a carbon footprint is. This statement is analogous to claiming “when a 500 tonne airplane flies from NYC to LA, it consumes the same amount of fuel whether I ride it or not (because the weight of a person is negligible compared to the weight of the plane). Thus my flying has no impact on the environment”. It is true that one person deciding to fly (or not) does not have an immediate effect on emissions. However, there is a footprint associated with a seat on a plane. And the market demand for flying, affects how the aviation industry schedules flights. In fact, if all of a sudden, lots more people wanted to fly, the aviation industry would not be able to all of a sudden schedule more flights overnight. However, the mining industry can respond much quicker to increases in demand, compared to the aviation industry. Miners even usually have older mining equipment which are no longer profitable to mine with (i.e. the electricity costs of running the equipment is greater than the financial rewards). But if demand goes up on the network, transaction fees also go up, and mining becomes more profitable to the extent that miners can respond quite quickly by turning on such older equipment [13]. More detail on calculating the footprint of individual transactions can be found in [22].

Mining is not primarily powered by renewables. One report produced by a crypto-investment agency [21] claims that (Bitcoin) mining is 75% powered by renewables. However, other independent (and arguably more thorough, as they include more regions and the changing seasons and miner migration) studies put the figure much lower at 29%–39% [13]. The data that I use to calculate emissions, includes usage of low-carbon energy sources weighted by hashrate of regions, with a global weighted average of ~40% lower-carbon energy production (0.58 KgCO2/kWh) — inline with this research. This is based on data from [7, 22], and the limitations of the accuracy of this approach is detailed in those links. (On a side note, using renewables is not a solution if it displaces others from using that renewable source [12]).

Mining is not primarily powered by surplus hydro-electric power in China. Emphasis mine: “There is a notion that electricity surplus in some APAC areas, such as the province of Sichuan in China, gives hashers who relocate their operations there during the rainy season [May-Oct/Nov] a competitive advantage in minimising their running costs. However, survey data demonstrates that this seasonal advantage appears to be offset by less affordable electricity prices throughout the rest of the year when hashers migrate back to other provinces, such as Xinjiang or Inner Mongolia in China. […] Coal-based mining is principally adopted in regions such as the Chinese provinces of Xinjiang and Inner Mongolia, and in Kazakhstan, whereas hydroelectric energy is mainly generated in South-Western regions of China (Sichuan and Yunnan). China’s oversupply of hydroelectric energy during the rainy season has often been used as evidence in claims that a vast majority of mining is powered by environment-friendly power sources. While it is true that the Chinese government’s strategy to ensure energy self-sufficiency has led to the development of massive hydropower capacity, the same strategy has driven public investments in the construction of large-scale coal mines. Like hydroelectric power plants, these coal power plants often generate surpluses. It should not come as a surprise then that a significant share of hashers in the region equally report using both hydropower and coal energy to power their operations”. p24, p27 [13].

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China’s mining distribution (for BTC) in Sep 2020. Note Sichuan (Hydro) is leading. [14]
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China’s mining distribution (for BTC) in Apr 2020. Note Xinjiang (Coal) is leading. [14]

Introduction

On SuperRare I’ve analyzed:

  • 17812 NFTs
  • 79977 transactions relating to these NFTs
  • 633 CryptoArtists

(I don’t know the total number of NFTs, transactions or artists on SuperRare, but I believe this is very close to almost all of them).

Background: how is the footprint calculated?

This is explained in more detail in [22].

Footprint per unit of Gas

These give[20] ¹ ³ :
Energy footprint per unit of Gas = 0.0005454743 kWh
Carbon footprint per unit of Gas = 0.0003182308 KgCO2

Update Mar 03 2021: The figures above are averages across the period Dec 2020 — Jan 2021, for when this study was conducted. Here are annual averages:

2017 (20 May–31 Dec): 0.0008427156 kWh, 0.0004916419 KgCO2
2018 (01 Jan–31 Dec) : 0.0011741214 kWh, 0.0006849847 KgCO2
2019 (01 Jan–31 Dec) : 0.0005121816 kWh, 0.0002988077 KgCO2
2020 (01 Jan–31 Dec) : 0.0003735465 kWh, 0.0002179278 KgCO2
2021 (01 Jan–01 Mar ): 0.0006310654 kWh, 0.0003681648 KgCO2

Footprint per transaction type

Different kinds of NFT transactions have different complexities, and thus different Gas requirements. While the values fluctuate, on SuperRare they are typically in the range:

Minting: 260K Gas => 142 kWh, 83 KgCO2
Bids:
75K Gas => 41 kWh, 24 KgCO2
Cancel Bid
: 22K Gas = > 12 kWh, 7 KgCO2
Sale: 160K Gas => 87 kWh, 51 KgCO2
Transfers:
95K Gas => 52 kWh, 30 KgCO2

Calculating footprint of NFTs

I believe this provides a lower-bound for the energy consumption of that NFT being tracked on the Ethereum network.

From what I can tell, SuperRare uses (at least) three smart-contracts, two for managing NFT ownership and transfers (v1 and v2), and the other for bids. They might also be using other contracts for doing other things which I have not come across yet. This would boost the numbers even higher.

Moreover, the contracts dealing with ownership is open-source, so querying it to get ownership and transfer related transactions is relatively trivial. The contract dealing with bids however, is closed-source. And without a so-called ABI (Application Binary Interface), I cannot programmatically query the contract for any bid transactions that involve a specific NFT. So instead I have to resort to more brute-force methods of search. And these are likely to miss transactions that are related to a particular NFT. Given that a transaction cannot use negative gas, any transactions that I do miss, would have pushed the numbers that I calculate even higher.

For this reason, I see the figures that I give as a lower-bound.

NiftyGateway however, is a bit different. They use one smart-contract per ‘collection’, and they don’t log bids or transfers on the blockchain unless the NFT is withdrawn from the platform. Minting does take place on the blockchain, and since it is the most expensive of the transactions, NFTs on NiftyGateway still have a high footprint. Especially when editions are taken into account, because each edition minted is an additional mint transaction (in large batches, the Gas per mint can drop from 260K to 210K, but for editions of 100s, this saving is then overriden by orders of magnitude).

Footprint per average NFT

Across 17812 NFTs, this gives an average of:
4.5 transactions, 369 kWh, 215 KgCO2 per NFT
http://cryptoart.wtf/#NFTs=1

(More statistics in the following sections)

Footprint per average transaction relating to a NFT

Note that this is more than double the 35 kWh of an average ETH transaction.

And I would again like to put out a reminder, that these figures relating to energy consumption and CO2 emissions, are only due to the tracking of bids and sales of the NFT on the blockchain. They do not include the production of the works, or even storage of the work online. Just the records of who owns what.

NFT Statistics

KgCO2 is computed from kWh, which is computed from Gas. So these are linearly correlated. Number of transactions however, is only indirectly correlated. As mentioned above, some transactions (such as minting) are more Gassy compared to others, such as bidding. So while NFTs with more transactions are more likely to have a higher footprint, there can be exceptions (e.g. a NFT with 5 sales and transfers could be higher than a NFT with no sales and transfers but more bids).

Energy consumption per NFT

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Carbon emissions per NFT

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NFT Age (time since being minted)

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Number of transactions per NFT

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Artist Statistics

Number of NFTs minted per artist

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Energy consumption per artist

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Carbon emissions per artist

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Carbon emissions per artist

Artist Age (time since joining platform)

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Income and revenue distributions

NFT primary sales

NFT secondary sales (10% goes to the artist)

Total revenue per NFT (including primary and 10% secondary sales)

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Artist primary sales

Artist secondary sales (10% goes to the artist)

Total income per artist (including primary and 10% secondary sales)

Though it wasn’t designed to apply at this scale, we can try looking at a metric of income inequality such as The Palma Ratio (PR) — a ratio of the top 10%’s share of income, compared to the bottom 40% (lower PR implies more equally distributed income, higher PR implies more inequality) [10].

The US’s PR is relatively high within the ‘Western’ world at 1.85. Japan and Denmark are more egalitarian at around 0.9. Countries like South Africa are amongst the worst with a PR of 7.The entire world’s PR — i.e. the income gap between the richest people in the world, compared to the poorest people in the world is 32.

SuperRare has a Palma Ratio of 29.

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Final thoughts

Footnotes

  1. It’s important to note, that while there are some very useful tools out there to calculate kWh and KgCO2 estimations for ETH wallets [9], these only look at the transactions that a ETH wallet was directly involved in (e.g. transfer of ETH funds). However, minting, sales and bids on an NFT are not necessarily linked to the authors’ ETH account depending on the platform used, so these tools will miss them. Instead, to calculate the footprint of an NFT, one must look at the smart-contract(s) involved. (Note that there may be more than one smart-contract involved for a single NFT, as it is on SuperRare: one contract for minting and transfers, another contract for bids).
  2. It might be more accurate to compute the energy consumption per unit of Gas at the time of the transaction, by using historical figures. However I don’t do this, and I use recent figures. The reason for this is because I’m less interested in the footprint of past NFTs, and I’m more interested in the footprint of current NFTs.
  3. Due to sheer volume, simple, typical, daily, activities also add up. A single email is thought to produce in order of ~1–10g of CO2. But just the CO2 emissions of spam emails were estimated to be around 3 billion KWh per year according to a report in 2009 [15].
  4. (moved to main body)

References

  1. https://www.etherchain.org/charts/transactionsPerDay
  2. https://www.etherchain.org/charts/totalGasUsage
  3. https://www.epa.gov/egrid/data-explorer
  4. https://www.eea.europa.eu/data-and-maps/daviz/co2-emission-intensity-6#tab-googlechartid_googlechartid_googlechartid_googlechartid_chart_11111
  5. https://www.iges.or.jp/en/pub/list-grid-emission-factor/en
  6. https://www.notion.so/Carbon-FYI-Methodology-51e2d8c41d1c4963970a143b8629f5f9
  7. https://ourworldindata.org/safest-sources-of-energy
  8. https://carbon.fyi/
  9. https://www.washingtonpost.com/news/wonk/wp/2013/09/26/wonkabroad/?arc404=true
  10. https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/publications/3rd-global-cryptoasset-benchmarking-study
  11. https://www.wired.com/story/bitcoins-climate-impact-global-cures-local/
  12. https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/publications/3rd-global-cryptoasset-benchmarking-study
  13. https://cbeci.org/mining_map
  14. https://cbeci.org/
  15. https://www.coincenter.org/estimating-bitcoin-electricity-use-a-beginners-guide/
  16. https://ethereum.org/en/developers/docs/gas
  17. https://medium.com/ethereum-grid/ethereum-101-how-are-transactions-included-in-a-block-9ae5f491853f
  18. https://eta-publications.lbl.gov/sites/default/files/lbnl-1005775_v2.pdf
  19. https://docs.google.com/spreadsheets/d/1hzzxMbytOZ1mYl9kLh_SvM6kne6JI_mdCfHIoNapr5M/edit?usp=sharing
  20. https://coinshares.com/research/bitcoin-mining-network-december-2019
  21. https://carbon.fyi/learn
  22. https://digiconomist.net/bitcoin-energy-consumption

computational ar̹͒ti͙̕s̼͒t engineer curious philomath; nature ∩ science ∩ tech ∩ ritual; spirituality ∩ arithmetic; PhD AI×expressive human-machine interaction;

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