=Paper=
{{Paper
|id=Vol-3791/paper29
|storemode=property
|title=Analysis of Blockchain Sustainability through the Comparison of Different Smart Contracts Programming Languages
|pdfUrl=https://ceur-ws.org/Vol-3791/paper29.pdf
|volume=Vol-3791
|authors=Stefano Bistarelli,Marco Fiore,Antonio Ignazio Lazzizera,Ivan Mercanti,Marina Mongiello
|dblpUrl=https://dblp.org/rec/conf/dlt2/BistarelliFLMM24
}}
==Analysis of Blockchain Sustainability through the Comparison of Different Smart Contracts Programming Languages==
https://ceur-ws.org/Vol-3791/paper29.pdf
Analysis of Blockchain Sustainability through the
Comparison of Different Smart Contracts Programming
Languages
Stefano Bistarelli1,† , Marco Fiore2,∗,† , Antonio Ignazio Lazzizera2,† , Ivan Mercanti1,† and
Marina Mongiello2,†
1
Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy
2
Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy
Abstract
This paper aims to analyze the correlation between programming languages used to implement smart contracts
and the related Blockchain platforms, seeking an economically and environmentally viable solution. The research
selects four programming languages commonly employed for smart contract creation, defining three standard
functions that will be tested on the Ethereum, Tezos, Solana, and Polkadot Blockchains. The study investigates
how these programming languages directly impact the amount of energy resources required and subsequently
influence the cost of executing a smart contract.
Keywords
Blockchain, Sustainability, Smart contracts, Comparison
1. Introduction
The emergence of the digital revolution has brought about various transformative technologies, but none
quite like Blockchain. This innovative technology can potentially revolutionize the market and security
vision that has characterized modern civilization. Blockchain technology is known for its exceptional
security, trust, decentralization, and community concepts, making it the most significant technology to
fundamentally change the market and security vision that has marked modern civilization.
Blockchain technology has diverse applications in various fields, such as healthcare [1], agri-food [2, 3],
election voting systems [4], and transactions [5]. Although Blockchain has significant potential and
interest, programmers and project proponents must address environmental sustainability [6] and carbon
footprint issues. They must keep the network running 24/7 with machines that harness energy resources
while minimizing the consumption of raw materials and ensuring a low-energy impact solution for
users while providing maximum efficiency [7].
One of the recent developments in Blockchain technology is the rise of smart contracts. These
contracts are written in different programming languages, which determine their complexity and,
consequently, the transaction’s cost. In this paper, we analyze cost by considering the smart contracts
based on different blockchains and various programming languages. This analysis will help identify
which of the blockchains is the most economical and sustainable in terms of energy for those who execute
them and the environment. The study will provide valuable insights into today’s most economical and
sustainable Blockchain technology.
6th Distributed Ledger Technology Workshop (DLT 2024), May 14-15, Turin, Italy
∗
Corresponding author.
†
These authors contributed equally.
Envelope-Open stefano.bistarelli@unipg.it (S. Bistarelli); marco.fiore@poliba.it (M. Fiore); a.lazzizera@studenti.poliba.it (A. I. Lazzizera);
ivan.mercanti@unipg.it (I. Mercanti); marina.mongiello@poliba.it (M. Mongiello)
Orcid 0000-0001-7411-9678 (S. Bistarelli); 0000-0003-0102-2394 (M. Fiore); 0000-0002-9774-1600 (I. Mercanti);
0000-0002-1477-1434 (M. Mongiello)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
2. Background
In this section, we present an overview of the blockchain, and we define their consensus protocol.
2.1. Blockchain type
The vast world of blockchain does not present one universal model for all types of uses. However, it
is divided into two different categories on which the significant blockchains are based: UTXO and
Account-based.
A UTXO, which stands for Unspent Transaction Output, is the amount of cryptocurrency obtained
by the recipient or saved by the sender as a result of a transaction on some blockchain; the amount of
each UTXO can then be ”spent” on a new exchange. The balance may be viewable in a crypto wallet, a
shared ledger with a unique address that reports information on all transactions in crypto.
An account is a structure used to identify users and smart contracts and verify the validity of
transactions made. Each account, specifically, is associated with a wallet address and a status containing
a set of information about the balance of crypto possessed by the user. When a transaction is initiated
on an account-based blockchain, the system verifies the amount of crypto possessed by the user who
initiated the transaction, ensuring that the wallet contains an equal or more significant number than the
amount to be sent. The account model can be compared, very simplistically, to a banking-type service.
A permissionless blockchain is a decentralized and distributed ledger that enables secure, transparent,
and tamper-proof transactions. It operates on a peer-to-peer network where all participants have equal
access to the network and its data and can participate in transaction validation. Since these blockchains
are public, anyone can join the network and validate transactions. The use of a public ledger, accessible
to all participants, increases accountability, enhances security, and strengthens trust, a fundamental
aspect of blockchains [8].
Private blockchains are not accessible to individual users without authorization. They are restricted
and usually limited to enterprise networks, providing higher levels of error control and transaction
validity.
2.2. Proof of work vs. Prof of stake
Like all technologies, blockchains are described and organized according to a set of rules defined
within the so-called ”Protocol.” A protocol in Blockchain is a set of rules, standards and algorithms that
govern the creation, validation and maintenance of a blockchain network. It defines the block structure,
consensus mechanism and validation process for transactions within the Blockchain. There are several
types, but the main distinction is made between the two main ones: Proof of Work and Stake.
Proof of Work is a protocol used to reach distributed consensus. It is based on finding a computationally
tricky number, but once found, it becomes easy for all other nodes to verify its correctness. In a system
using PoW, a block is valid only if it contains a valid solution to the PoW. Within this protocol, nodes in
the network compete to solve a complex mathematical problem, an inverse hash. Solving this problem
is a random process with very low probability, and the only way to find a valid PoW is to try all possible
combinations until the right one is found. The first miner who solves the problem has the right to
create the next block, earning a reward in cryptocurrency. Once the block is created, it is transmitted to
the network, waiting for other nodes to check its validity. The difficulty of the resolution is updated
periodically about the network of the network to keep the time required to generate a block as constant
as possible. The main advantage of Proof of Work is the firm guarantee of immutability.
The disadvantages of this protocol are:
• Massive energy consumption: as Bitcoin is the largest project using Proof of Work, it currently
consumes about 0.3% of the world’s electricity (19.69 GW per day1 ). About $1 million per day
between electricity and mining hardware.
1
https://ccaf.io/cbnsi/cbeci.
• Scalability difficulties: Proof of Work is one of the bottlenecks in scaling the system. However, it
is possible to make this blockchain scalable without changing the consensus algorithm, either by
adopting off-chain solutions or by changing the block size.
• Vulnerability to a 51% attack: If a miner reaches 51% of the network’s total computing power,
it could create blocks faster than the remaining miners. Together, the miner in question could
reverse or modify some transactions.
Proof of Stake is another protocol used within blockchains. It serves the same purpose as PoW, but
the process to achieve the end goal is different. In PoS, validators are alternated, chosen in advance
based on the amount of cryptocurrency they hold for the relevant blockchain, also referred to as a stake.
Users in possession of tokens can stake their tokens to have, in return, the right to confirm a blockchain
transaction and receive a reward by dividing validators. The creator of a new block is then chosen in
advance, using a combination of different parameters depending on the type of algorithm used. PoS is
more efficient because complex calculations need not be followed for each new block, and attacks are
more expensive. PoS is also vulnerable to a 51% attack. An attacker, in this case, will not need 51% of
the total, but 51% of the total tokens. However, if an attacker tried to buy so many tokens, the market
would react with a rapid increase in the price of the tokens. Finally, PoS is, therefore, much cheaper
as there are no elevated electricity costs (680.33 kW per day on Ethereum2 ) and powerful hardware.
A blockchain-based on Proof of Stake can efficiently run even on hardware with low computational
capabilities, such as a Raspberry. This is the most widely used protocol in blockchains today.
2.2.1. Smart contract
A smart contract is a contract that governs the terms and conditions of an agreement between parties.
However, unlike a traditional contract, the terms of a smart contract are executed based on a code
programmed on a blockchain that mechanically complies with the terms of a legally binding agreement.
The advantages over traditional contracts are reduced risks, lower administrative costs and more
efficient business processes. A smart contract cannot be executed without payment of a fee, which is
measured in terms of gas. Gas refers to the amount of computational work that miners or validators
require in order to authorize transactions or execute smart contracts. Gas fees are valued in gwei on
Ethereum, where one gwei is equivalent to a certain amount of ETH. The cost of gas fees is not fixed
but depends on various defined parameters such as the blockchain protocol, functions implemented in
the smart contract, and the programming language used to develop it.
Gas fees work on the laws of supply and demand: by offering a higher fee, validators will be
incentivized to process the transaction faster. A portion of the gas fees can also be awarded as a
premium to the validator who completes the transaction first. These fees are critical to the proper
functioning of the network, much like gasoline in a car, ensuring the stability and safety of the system.
When developing smart contracts and blockchain-based apps, it is essential to consider the unique
limitations and features required by blockchain technology. Identifying and investigating all these
changes is necessary to build a complete body of knowledge based on blockchain software engineering.
3. Proposed approach
Our research analyses smart contracts across various blockchains and uses different programming
languages to evaluate their costs. This analysis will help identify the most cost-effective and energy-
efficient blockchain for those who run it and the environment in which it operates. Moreover, we
analyze how the use of different programming languages for writing smart contracts on various
blockchains affects the transaction gas cost, defining which among those considered are more cost-
effective. Regarding sustainability, we also consider the environmental impact of these blockchains in
terms of electricity consumption and CO2 emissions. The chosen programming languages vary in type
2
https://ccaf.io/cbnsi/ethereum.
to enable a comparison between high and low levels, and consequently, the blockchains that utilize
them have been selected. For all programming languages used in smart contract writing, the analyzed
blockchains are all permissionless.
Private blockchains are not included in the analysis because they are not accessible to individual
users without authorization.
Chosen blockchains are summarized below:
• Ethereum and Solidity
Ethereum, created by Vitalik Buterin in 2013, revolutionized blockchain with its programmable
smart contracts. Operating as a permissionless public blockchain, Ethereum has transitioned to a
Proof of Stake consensus protocol in 2023. Its native token, ETH, fuels platform activities and
facilitates value exchange. Ethereum’s pivotal role extends beyond cryptocurrency, powering
the burgeoning decentralized finance (DeFi) sector. Advantages include a deflationary token
supply, a robust community fostering demand, passive income opportunities through staking,
and serving as foundational infrastructure for emerging projects like Non-Fungible Tokens
(NFTs). Solidity, a high-level programming language primarily for Ethereum, facilitates smart
contract development. Inspired by C++, Python, and JavaScript, Solidity interfaces seamlessly
with the Ethereum Virtual Machine (EVM). Developers leverage Solidity to craft smart contracts
governing various functionalities, including voting mechanisms and multi-signature wallets.
Solidity programming necessitates Solidity compilers, such as Remix and npm, tailored for Linux
and MacOS environments.
• Tezos and SmartPy
Tezos, introduced in 2014, offers innovative features surpassing traditional blockchains like
Ethereum. Its Liquid Proof-of-Stake (LPoS) consensus protocol allows for decentralized smart
contract execution and governance through a voting mechanism. Tezos adaptability enables
dynamic adjustments to its protocol parameters, enhancing security through formal methods. The
native cryptocurrency, XTZ, fuels transactions within the ecosystem. Tezos architecture comprises
multiple layers, with a peer-to-peer layer ensuring network connectivity and a subsequent layer
treating the network as a distributed database. Blocks are extracted, modified, and passed to the
economic protocol layer, responsible for consensus enforcement. SmartPy, a Python-like high-
level language, simplifies smart contract development on Tezos. It offers a user-friendly syntax and
a secure programming environment. Initially, smart contracts on Tezos were coded in Michelson,
a low-level language focused on security and precision. SmartPy’s compiler seamlessly translates
code into Michelson for testing and deployment onto the blockchain, enhancing developer
efficiency and contract reliability.
• Polkadot and Rust
Polkadot, established in 2017, revolutionizes blockchain interoperability with its Nominated Proof
of Stake (NPos) consensus mechanism. The network features a primary relay chain governing
inter-chain communication and numerous user-created parachains operating autonomously
within the Polkadot ecosystem. Polkadot boasts a throughput capability of 1,000 transactions
per second. Rust, developed by Mozilla Research, epitomizes modern systems programming
by seamlessly blending low-level performance control with high-level convenience and robust
security assurances. It excels in speed and memory efficiency, making it suitable for critical
performance services and embedded systems, while its advanced type system and ownership
model ensure memory and thread safety, minimizing bugs at compile time. Renowned for its eco-
friendly attributes, Rust stands out as one of the most environmentally sustainable programming
languages in use today.
• Solana and C++
Solana, introduced in 2018, stands out as a blockchain platform optimized for widespread adoption,
catering to diverse sectors such as finance, NFTs, payments, and gaming. Operating as a global
state machine, Solana is distinguished by its high-performance architecture, open nature, and
decentralized ethos. Its native cryptocurrency, SOL, drives transactions within the ecosystem.
Solana’s innovative Proof of History (PoH) consensus mechanism ensures verifiable event order
and time intervals, fostering trust without reliance on external entities or synchronized clocks.
C++, renowned for its versatility and efficiency, serves as an ideal programming language for
Solana development. Combining low-level capabilities with high-level functionalities, C++ en-
ables seamless integration with system libraries, making it a preferred choice for video game
development, AR/VR applications, IoT devices, and operating systems. Notably, C++ boasts
exceptional energy efficiency attributed to its minimal storage usage, further enhancing its appeal
for Solana development.
3.1. Smart contracts definition
The selection of functions to analyze within smart contracts remains a critical aspect of the comparison.
Due to the heterogeneous nature of the chosen programming languages, defining the programs to
execute proved to be challenging, as not all languages support certain high or low-level functionalities,
object-oriented programming, or other features. Therefore, the decision was made to opt for very basic
projects to achieve a satisfactory overall understanding.
The chosen functions, ordered by increasing complexity, are as follows:
• Sum of two numbers: we test how different programming languages manage the sum of two
integers number, being it a mathematical primitive in equations. This primitive is shown in [9].
• Conversion of an integer into a string: we aim to analyze the behaviour of each Blockchain to a
cast operation, as indicated in [10].
• Creation of a personal data record for a hospital patient: the goal of this contract is to verify the
reaction of tested platforms with the management of a structure composed by strings and integers.
Healthcare is between the main applications for evaluating smart contracts, as highlighted in
[11].
Each function has been implemented in a smart contract written for every analyzed Blockchain. A
total of 12 smart contracts have been written and tested.
4. Tests and results
This Section will show all the tests conducted on the selected blockchain and the related results.
Ethereum - Solidity For the Ethereum blockchain, Remix IDE was utilized to conduct all test cases.
Remix IDE is a configuration-free tool featuring a GUI for smart contract development. It is employed
by both experts and beginners, facilitating a straightforward deployment process on any chosen chain.
All tests were simulated using virtual cryptocurrencies within a testnet provided by the IDE. This
approach ensured a controlled environment for experimentation and validation of smart contracts on
the Ethereum blockchain.
Tezos - SmartPy For the Tezos Blockchain, SmartPy IDE was selected. SmartPy IDE provides a
comprehensive online environment for developing, testing, and deploying smart contracts on the Tezos
Blockchain, all within the familiar Python syntax. Simulation was conducted on a test network called
Ghostnet, which is popular for testing contracts without spending real cryptocurrencies.
Polkadot - Rust For the analysis of Polkadot, a framework similar to Remix for Ethereum, Substrate,
was employed. Substrate executes the development of Blockchain applications by providing developers
with a versatile toolkit that overcomes the constraints typically encountered in other frameworks.
Unlike rigid frameworks that impose predefined structures, Substrate offers a flexible and modular archi-
tecture, empowering developers to tailor the blockchain infrastructure precisely to their project’s needs.
Table 1
Results of contracts execution, in gas, in each chosen Blockchain
Blockchain Smart contract language Integers sum Cast operation Healthcare scenario
Ethereum Solidity 328 1910 11681
Tezos SmartPy 367 1033 9112
Polkadot Rust 903 2416 13006
Solana C++ 299 4591 17467
Substrate’s agility stems from its design philosophy, which prioritizes adaptability and customization.
Its modular nature allows developers to effortlessly integrate and customize components, enabling the
seamless implementation of complex functionalities. By leveraging Substrate, developers can expedite
the development process, reduce overhead costs, and enhance the scalability and interoperability of
their Blockchain solutions.
Solana - C++ A local testing environment has been developed for Solana analysis. The tool used
for testing was SolanaLabs, a local framework-like tool enabling the evaluation of various aspects of a
contract for development and configuration. For the testnet, SolanaTestnet, provided by Solana, proved
to be ideal for testing the smart contracts. Lastly, the Mathwallet, a local wallet, was utilized. It was
populated with SOL using the SolanaDevnetFaucet.
4.1. Collected gas fees
We collect the spent gas for deploying each contract in a Blockchain. Results are summarized in Table 1.
Fig. 1 shows the gas fee comparison between the analyzed platforms. The trend depicted in the
figure is nearly linear across all languages. Costs are significantly low when dealing with the sum
smart contract. This can be attributed to the minimal gas required for the transaction since only a few
low-level functions are used, resulting in low gas consumption. Upon closer inspection, intersections of
graphs are visible, particularly in the case of the sum contract. This can be attributed to the nature of
programming languages. C++, being a low-level language, enables operations directly on memory, thus
requiring minimal gas for execution on the blockchain. The scenario changes when considering the
cast smart contract. Here, high-level languages like SmartPy and PyTeal prove to be more cost-effective
as they possess built-in syntax, commands, and functions for converting an integer to a string with
just a single line of code. Conversely, low-level languages incur higher costs due to multiple and
resource-intensive register operations. For the healthcare smart contract, the overall cost trend becomes
clearer. Here, creating a Patient object creates some differences in different languages. Low-level and
hybrid languages like Rust need to rely on external or more complex functionalities, leading to higher
resource consumption on the chain.
4.2. Sustainability analysis
In this section, we present an analysis of various blockchain networks regarding their annual transaction
volume, energy consumption, and energy cost per transaction. Table 2 shows the results of the analysis.
Table 2
Analysis of CO2 emission for each analyzed Blockchain
Blockchain Transactions per year Power consumption [GWh] CO2 emission [kg]
Ethereum 4.9e10 7.210 2784143
Tezos 1,2e8 1.010 302461
Polkadot 3,1e6 0.473 122275
Solana 3,3e8 5.961 2228750
Figure 1: Gas spent for each Blockchain
All the parameters are strongly influenced by multiple factors, primarily the consensus protocol,
which, even though based on PoS, has various variants that characterize emissions. Regarding power
consumption, the values vary widely, which is justifiable due to each blockchain’s popularity: the more
users utilize them, the more energy consumption is affected. In direct proportion, data about CO2
emissions can be derived. However, this data significantly varies depending on the energy sources used
to operate the nodes within the chain.
Figure 2: CO2 emission per transaction for each analyzed Blockchain
Thanks to official data gathered from different sources3 , it is possible to create a graph regarding
emissions per transaction, as shown in Fig. 2. Some values, instead, were calculated by knowing
the number of transactions and the total estimated emission for the year 2022. A clear difference
in ecological impact data can be observed. As blockchain with lower CO2 emissions, Tezos stands
out. Tezos’ low carbon footprint means that developers and users can prioritize innovation without
compromising sustainability. Being a platform designed to evolve through its on-chain governance
3
https://etherscan.io/, https://indices.carbon-ratings.com/,https://greenpolkadot.io/, https://www.theblock.co/data/
crypto-markets/spot,https://indices.carbon-ratings.com/
mechanism, Tezos’ efficiency is not accidental but designed. This flexible design allows the blockchain
to adapt to future needs and grow based on users’ requirements on the platform. In fact, Tezos’
blockchain has increased energy efficiency per transaction by at least 70%, with an estimated energy
requirement per transaction being less than 30% in 2021 compared to that of 20204 . Regarding Polkadot’s
consumption, this was possible to derive by calculating, through multiple block explorers, the number of
daily transactions, averaging them annually. The total includes transactions executed on the relay-chain
and parachains. Polkadot is designed to power the next big wave of web innovation without the high
energy consumption of traditional proof-of-work blockchains. The innovative consensus protocol
consumes a small fraction of the energy consumed by conventional blockchains5 . In conclusion, the
last two blockchains, Solana and Ethereum, have very similar consumption levels. Ethereum has
long assessed and analyzed consumption, thus deciding to undergo a transition called the ’Merge’,
radically modifying its consensus protocol, which was very energy-intensive and consequently also
carbon emissions: from PoW to PoS. This reveals itself as one of the most intelligent choices given the
blockchain’s vast capabilities and popularity, which, behind the famous Bitcoin, serves as a model for
all new projects. The Solana Foundation, on the other hand, is committed to studying the impact of the
Solana blockchain, making data public and adopting measures to reduce the chain’s footprint to zero.
Solana is the first Layer 1 blockchain with smart contract capability with real-time energy emissions
monitoring, allowing anyone worldwide to examine the network emissions down to the validator or
RPC level6 .
5. Related Work
BLOCKBENCH [10] was introduced in 2017 as the first evaluation framework for analyzing private
blockchains in a fair and in-depth manner. The framework enables a better understanding of various
system design choices and enables an objective comparison between different platforms. Integrating
any private blockchain into BLOCKBENCH is a simple process which can be accomplished via its APIs.
BLOCKBENCH provides performance evaluation, measuring overall and component-wise performance
in terms of throughput, latency, scalability and fault tolerance. The authors used BLOCKBENCH
to comprehensively evaluate three major private blockchains: Ethereum (as a solidity blockchain),
Parity, and Hyperledger Fabric. The results suggest that there is still significant room for improvement
before these systems become viable replacements for current database systems in traditional data
processing workloads. Furthermore, the assessment highlights performance gaps among the three
systems attributed to the design choices at different blockchain software stack levels.
In [12], the authors have used a benchmarking approach in their research and shared the preliminary
results for the Python Ethereum client running on a Mac. The study reveals that there can be significant
differences in the reward per CPU second for functions in Ethereum’s most popular contracts, which
can result in misaligned incentives that impact the dependable operation of the blockchain. Additionally,
the research highlights that contract creation, done once for each new contract, can be more lucrative
than the regular execution of contract functions.
In 2019, [13] presents a comparative analysis of various distributed ledger technology (DLT) platforms
in a diplomatic and unbiased manner. The selection of platforms is based on their popularity, current
market share, and evolving trends and approaches. The platforms selected for the analysis are Ethereum,
EOS, Hyperledger Sawtooth, and NEO. The comparison is done from both development and performance
perspectives to provide a comprehensive understanding of their strengths and limitations. The analysis
reveals that Sawtooth offers significant customization capabilities that may affect performance, while
EOS maintains stable throughput under varying network scales and loads.
[11] objectively evaluates and compares different smart contract functions. The article suggests using
multi-criteria analysis (MCA) to assess and compare functions based on multiple criteria to ensure a
4
https://tezos.com/carbon
5
https://polkadot.network/features/technology
6
https://solana.com/environment
fair evaluation process. The study provides a comprehensive review of the current state-of-the-art
in the field by considering various criteria used in the selection process, such as security, scalability,
and performance. It also highlights the challenges associated with critical criteria for smart contract
selection, including security, privacy, efficiency, scalability, and regulatory concerns. However, the
article stresses that the process is complicated by challenges such as the lack of standardization and
difficulty comparing platforms. The article emphasizes the need for further research on smart contract
platforms’ long-term performance and scalability and more comprehensive and objective evaluation
methods for MCA of smart contract selection while acknowledging the complexity of the subject matter.
The authors of [9] have proposed a multi-objective test selection technique for smart contracts
that aims to balance three crucial objectives: time, coverage, and gas usage. They comprehensively
evaluated their approach using five solidity smart contracts based on data collected from GitHub and
State of the DApps7 . They compared their results with various test selection methods in traditional
software systems. Through statistical analysis of their experiments, which utilized benchmark Solidity
smart contract case studies, the authors have demonstrated that their approach significantly reduces
the testing cost while maintaining acceptable fault detection capabilities. These findings have been
compared to random search, mono-objective search, and the traditional re-testing method that does not
employ heuristic search.
With respect to current state of the art, this paper analyzes different public Blockchains and program-
ming languages, with the final goal to understand the impact of a language on energy consumption
requirements.
6. Conclusion
The in-depth analysis conducted on smart contract dynamics reveals a complex landscape where
programming languages play a significant role, especially when it comes to low-level languages. These
languages can directly influence the efficiency and optimization of operations performed by smart
contracts on a blockchain. Although they are faster, do not require compilers, and use minimal
memory, they rely on external functionalities that compromise the final cost. Another significant
contribution comes from the efficiency of the blockchains on which smart contracts operate. Regarding
the actual costs incurred for executing a smart contract on a blockchain, these are still influenced by the
blockchain itself: governance policies and resources employed by the operating logic make prices vary
significantly. The intrinsic characteristics of the blockchain and the adopted consensus protocol play a
predominant role in determining the environmental footprint. The decentralized and diversified nature
of consensus protocols can substantially impact energy consumption and CO2 emissions associated
with smart contract execution. Although careful programming can contribute to optimizing smart
contract efficiency, it is the fabric of the blockchain itself and the consensus rules that predominantly
influence carbon emissions.
In summary, while programming languages play a significant role in the internal optimization of
smart contracts, the broader context of the blockchain structure and the consensus protocol largely
dictates the environmental impact of smart contract-related activities. Additionally, considerations
must be made regarding the cryptocurrency market and its daily fluctuations, influenced by global
stock markets. Prices and consumption are just some of the aspects to consider when developing a
decentralized project or application. For a comprehensive overview, perspectives on the project’s
blockchain growth, upcoming implementations, and community support should also be evaluated to
ensure foresight and backing from the community. Nearly all platforms analyzed, regardless of the
programming language for smart contracts, are exploring and testing substantial changes to align with
global emission reduction programs.
The conducted analysis is a first step in making a deep analysis on smart contracts execution and
Blockchain platforms sustainability in different scenarios. Future developments regard the inclusion
7
https://www.stateofthedapps.com.
of more Blockchains and smart contracts with different programming languages, together with the
development of an automated tool that calculates Blockchain consumptions with a smart contract given
by the user.
Acknowledgments
S. Bistarelli and I. Mercanti are members of the Gruppo Nazionale Calcolo Scientifico-Istituto Nazionale
di Alta Matematica (GNCS-INdAM). This work has been partially supported by:
• GNCS-INdAM, CUP_E53C23001670001;
• European Union - Next Generation EU PNRR MUR PRIN - Project J53D23007220006 EPICA:
“Empowering Public Interest Communication with Argumentation”;
• University of Perugia - Fondo Ricerca di Ateneo (2020, 2021, 2022) - Projects BLOCKCHAIN4FOOD-
CHAIN, FICO, AIDMIX, “Civil Safety and Security for Society”;
• European Union - Next Generation EU NRRP-MUR - Project J97G22000170005 VITALITY: “Inno-
vation, digitalisation and sustainability for the diffused economy in Central Italy”;
• Piano di Sviluppo e Coesione del Ministero della Salute 2014-2020 - Project I83C22001350001 LIFE:
“the itaLian system Wide Frailty nEtwork” (Linea di azione 2.1 “Creazione di una rete nazionale
per le malattie ad alto impatto” - Traiettoria 2 “E-Health, diagnostica avanzata, medical devices e
mini invasività”).
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