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Press Release: Ethereum Blockchain Eliminates 99.99% of its Carbon Footprint Overnight After a Successful Merge According to New Report

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Press Release: Ethereum Blockchain Eliminates 99.99% of its Carbon Footprint Overnight After a Successful Merge According to New Report

Posted | Updated by Insights team:

Publication | Update:

Sep 2022
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A new report from CCRI (Crypto Carbon Ratings Institute), commissioned by ConsenSys, reveals that the transition from Proof of Work to Proof of Stake has reduced the electricity consumption and carbon footprint of the Ethereum network by over 99.988 % and 99.992%, respectively.

Today, ConsenSys confirms that the goal of making Ethereum more sustainable through a historic transition from the Proof of Work to a Proof of Stake consensus mechanism has been achieved. This upgrade transforms Ethereum, the world’s first and largest smart contract platform, into an almost net-zero technology positioned for sustainable future growth, reducing overnight its carbon footprint by over 99.99%, according to a new report from CCRI (Crypto Carbon Ratings Institute), commissioned by ConsenSys. This surpasses the 99.95% estimate from the Ethereum Foundation.

According to CCRI, Ethereum’s electricity consumption has reduced by over 99.988%, from nearly 23 million megawatt-hours per year to just over 2,600. As a result, CO2 emissions are down 99.992%, from over 11 million tons annually to under 870, which is the equivalent of less than the annual energy use for a hundred homes in the United States.

The biggest decarbonization in the history of tech paves the way for industries

The Merge represents an extraordinary engineering feat on the part of Ethereum’s core developers – a unique and complex upgrade made possible by years of research and testing. It is the first time in history that an operational blockchain network has changed its consensus model while in continuous operation, dramatically slashing its carbon footprint overnight. Moreover, the Merge was carried out in a way that was entirely seamless for users, without any downtime.

The collaboration of hundreds of developers from all over the world, often working on a voluntary basis, is an interesting example of collective action to improve a public good and could provide a model for other industry overhauls in the future. It demonstrates how innovation and technology improvement can radically reduce emissions. Similar radical innovation and efforts are inevitable also in other sectors to achieve deep decarbonization. The slow progress of nations to decarbonize in line with the Paris Agreement underpins the necessity to act now and follow the example of Ethereum.

The Merge is the second implementation in a three-phase plan designed to make Ethereum more sustainable and secure. The transition to Proof of Stake sets the foundation for these next pivotal stages in the Ethereum development roadmap.

Speaking of the report and the success of the transition, Joseph Lubin, founder of ConsenSys and co-founder of Ethereum, said, “We’re delighted to have commissioned this report from CCRI, which substantiates the Ethereum Merge’s impact as likely the biggest decarbonization effort of any industry in history. Having removed the high carbon footprint as one of the biggest barriers to future growth, Ethereum is now primed for further waves of interest, development, adoption, and investment, as The Merge enables Ethereum to become internet scale IT infrastructure for low carbon projects around the globe.”

Uli Gallersdörfer, Co-founder and CEO of CCRI, stated, “We’re pleased to have been able to leverage our expertise to evaluate the success of Ethereum’s transition to Proof of Stake in sustainability terms and to have such positive findings. As a result, Ethereum’s green credentials are now comparable to any of the newer platforms launched based on Proof of Stake from the outset.” 

The Merge opens a vast horizon of new opportunities for brands

The carbon footprint of the blockchain and cryptocurrency sector, particularly Proof of Work networks, has come under increasing scrutiny. At the same time, blockchain innovations like NFTs and decentralized finance have gained prominence and sizable user bases.

Ethereum’s transition to Proof of Stake could not be more timely. The move paves the way for adopting Ethereum-based applications and tokens by groups who would otherwise have been deterred by the high carbon footprint, allowing them to participate in the vast global network of Ethereum-based apps and services. For example, more complex smart contracts, such as those used to power NFTs or enterprise applications, invariably rely on more code to transact. Under Proof of Work, the environmental price of using these applications was simply too great given the current state of the power sector decarbonization and typical mining locations. Under Proof of Stake, users can transact with NFTs or use complex smart contracts with just a fraction of the impact.

In carrying out this research, CCRI used established literature and methodologies for the Proof of Work component, while the Proof of Stake assessment was conducted using a research framework developed by CCRI and adapted for Ethereum’s specific landscape.

The full CCRI report is available for download at https://carbon-ratings.com/eth-report-2022.

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Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

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As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

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Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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