LP-801: Carbon Accounting Methodology

Abstract

This LP defines the methodology for measuring, calculating, and reporting greenhouse gas (GHG) emissions associated with Lux Network operations. It aligns with the GHG Protocol Corporate Standard and provides specific guidance for blockchain network carbon accounting.

Motivation

Accurate carbon accounting is foundational to credible sustainability claims. Without rigorous methodology:

1. Greenwashing risk - Vague claims invite skepticism and regulatory action
2. Incomparable metrics - Stakeholders cannot benchmark against other networks
3. Ineffective reduction - Cannot improve what isn't measured
4. Investor distrust - ESG-focused capital requires verified emissions data

This LP establishes the accounting foundation that enables all downstream environmental commitments. By aligning with GHG Protocol, we ensure compatibility with institutional reporting requirements and carbon market mechanisms.

Scope

Organizational Boundary

Control Approach: Operational control

Lux Network accounts for emissions from:

• Protocol development and maintenance operations
• Validator network coordination
• Foundation/DAO operations

Operational Boundary

Scope	Included Sources	Methodology
Scope 1	Direct emissions	Not applicable (no owned facilities/vehicles)
Scope 2	Purchased electricity	Validator node operations
Scope 3	Value chain emissions	Categories 1, 3, 5, 6, 11

Scope 2: Validator Network Emissions

Calculation Methodology

Energy Consumption Estimation

Formula:

E_network = Σ (N_validators × P_average × H_operating × PUE)

Where:

• N_validators = Number of active validators
• P_average = Average power consumption per validator (kW)
• H_operating = Operating hours per period
• PUE = Power Usage Effectiveness of hosting facility

Reference Values

Validator Type	Power Consumption	Source
Standard node	150-300W	Hardware specifications
High-performance node	300-500W	Hardware specifications
Cloud instance (c5.xlarge)	~100W equivalent	AWS/GCP estimates

Emissions Calculation

Location-based method:

CO2e_location = E_consumed × EF_grid

Market-based method:

CO2e_market = E_consumed × EF_supplier - RECs_retired

Where:

• EF_grid = Grid emission factor (kg CO2e/kWh)
• EF_supplier = Supplier-specific emission factor
• RECs_retired = Renewable Energy Certificates retired

Emission Factors

Region	Grid Factor (kg CO2e/kWh)	Source
US Average	0.417	EPA eGRID 2023
EU Average	0.276	EEA 2023
Nordic	0.030	IEA 2023
Global Average	0.490	IEA 2023

Validator Survey Methodology

1. Annual survey to all registered validators
2. Required data:
   • Hardware specifications
   • Hosting location (country/region)
   • Energy source (if known)
   • Renewable energy purchases
3. Response rate target: >50% of stake-weighted validators
4. Gap filling: Use regional averages for non-respondents

Scope 3: Value Chain Emissions

Category 1: Purchased Goods and Services

Item	Methodology	Emission Factor Source
Cloud services	Spend-based	Supplier reports
Software licenses	Spend-based	EEIO factors
Professional services	Spend-based	EEIO factors

Category 3: Fuel and Energy-Related Activities

Activity	Methodology
T&D losses	Grid average loss factor × Scope 2
Upstream fuel	Well-to-tank factors

Category 5: Waste Generated in Operations

Waste Type	Methodology
E-waste (validators)	Weight-based, hardware lifecycle
Office waste	Spend-based estimate

Category 6: Business Travel

Mode	Methodology	Data Source
Air travel	Distance-based	DEFRA factors
Ground travel	Distance-based	DEFRA factors
Hotels	Night-based	HCMI factors

Category 11: Use of Sold Products

Not applicable - Lux Network is infrastructure, not a product manufacturer.

However, we report:

• Energy consumption enabled by the network
• Emissions intensity per transaction

Intensity Metrics

Per-Transaction Metrics

Formula:

I_tx = (Scope2_network + Scope3_relevant) / N_transactions

Reported as:

• gCO2e per transaction
• kWh per transaction

Per-TVL Metrics

Formula:

I_tvl = Total_emissions / TVL_average

Reported as:

• kgCO2e per $1M TVL

Data Quality

Quality Scoring

Score	Description	Acceptable Use
1	Primary data, externally verified	All scopes
2	Primary data, internally verified	All scopes
3	Secondary data, industry average	Scope 3 only
4	Estimates, proxy data	Scope 3, flagged
5	Extrapolation, modeling	Sensitivity analysis only

Uncertainty Quantification

Report uncertainty ranges:

• High confidence: ±10%
• Medium confidence: ±25%
• Low confidence: ±50%

Reporting Requirements

Annual GHG Report

Contents:

1. Executive summary
2. Methodology overview
3. Scope 1, 2, 3 emissions by category
4. Intensity metrics
5. Year-over-year comparison
6. Reduction initiatives
7. Targets and progress
8. Data quality statement
9. Verification statement (if applicable)

Quarterly Updates

• Network energy consumption
• Validator survey results
• Key intensity metrics

Verification

Internal Verification

1. Cross-check calculations
2. Validate emission factors
3. Review data quality scores
4. Sign-off by Sustainability Lead

External Verification

Target: Annual third-party verification per ISO 14064-3

Scope: Limited assurance (Year 1), Reasonable assurance (Year 3+)

Reduction Targets

Science-Based Targets

Aligned with SBTi guidance:

Target	Baseline	2025	2027	2030
Scope 2 intensity	TBD	-20%	-50%	-100%
Renewable energy	TBD	50%	80%	100%

Reduction Strategies

1. Validator incentives for renewable energy use
2. Geographic distribution toward low-carbon grids
3. Efficiency improvements in consensus protocol
4. REC/carbon offset procurement for residual emissions

Offsets Policy

Hierarchy

1. Avoid: Efficient protocol design
2. Reduce: Clean energy, efficient hardware
3. Offset: Only for residual, unavoidable emissions

Offset Quality Criteria

• Verified under recognized standard (Gold Standard, Verra VCS)
• Additional and permanent
• No double counting
• Preferably removal-based (not avoidance)

Blockchain-Specific Considerations

Proof-of-Stake Efficiency

Lux uses proof-of-stake consensus, which is:

• ~99.9% more efficient than proof-of-work
• No energy-intensive mining
• Validator hardware is general-purpose servers

Network Growth Accounting

As network grows:

• More validators = more energy
• More transactions = lower per-tx emissions (efficiency gains)
• Track both absolute and intensity metrics

Comparison Methodology

When comparing to other networks:

• Use consistent boundaries
• Normalize by transaction count and finality
• Account for security model differences

Related LPs

• LP-800: ESG Principles and Commitments
• LP-810: Green Compute & Energy Procurement
• LP-820: Network Energy Transparency
• LP-850: ESG Standards Alignment Matrix

Changelog

Version	Date	Changes
1.0	2025-12-17	Initial draft

Copyright

Copyright and related rights waived via CC0.