Bureau Veritas Sample Verification Report — Sensor-Based MRV Output

Document Control

• Version: 1.0
• Date: [Insert Date]
• Author: Bureau Veritas Compliance Team
• Approved by: [Insert Approver Name]
• Document Reference: BV-SVR-2023-001

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Table of Contents

1. [Project Summary](#project-summary)
2. [Methodology](#methodology)

• 2.1 [Data Collection](#data-collection)
• 2.2 [Data Processing](#data-processing)
• 2.3 [Verification Process](#verification-process)

1. [Measurement Data](#measurement-data)

• 3.1 [Data Formats](#data-formats)
• 3.2 [Data Field Mappings](#data-field-mappings)

1. [Verification Findings](#verification-findings)
2. [Conclusion](#conclusion)

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1. Project Summary

This verification report outlines the assessment of DaedArch Corporation's sensor-based Measurement, Reporting, and Verification (MRV) platform for carbon market applications. The project aims to validate the accuracy and reliability of the environmental data captured by DaedArch's IoT sensors, ensuring compliance with the Bureau Veritas standards for greenhouse gas (GHG) inventories and carbon projects.

1.1 Objectives

The primary objectives of this verification are:

• To confirm that the sensor data meets the requirements set forth by Bureau Veritas for GHG reporting.
• To evaluate the integrity of the data processing algorithms utilized by DaedArch.
• To ensure full compliance with the CORSIA verification standards applicable to the aviation industry.

1.2 Scope of Verification

The scope of this verification includes:

• Evaluation of data collection methodologies.
• Assessment of data processing and reporting formats.
• Verification of data integrity and accuracy against established benchmarks.

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2. Methodology

2.1 Data Collection

Data collection shall be performed using DaedArch's IoT sensors deployed across various project sites. The following standards shall be adhered to during data collection:

• Sensor Calibration: All sensors shall be calibrated in accordance with ISO 17025 standards prior to deployment.
• Data Frequency: Data shall be collected at intervals not exceeding 15 minutes to ensure temporal accuracy.
• Chain of Custody: A full chain-of-custody protocol shall be maintained, documenting sensor deployment, data retrieval, and data processing.

2.2 Data Processing

Data captured by the sensors shall be processed using certified algorithms that comply with the following specifications:

• Algorithm Certification: Algorithms must be certified according to ISO 14064-3 standards.
• Data Processing Pipeline: The following steps shall be followed in the data processing pipeline:

1. Raw Data Acquisition: Sensor data is collected and timestamped.
2. Data Validation: Initial data validation checks for outliers and anomalies.
3. Data Normalization: Data is normalized to account for environmental variables (e.g., temperature, humidity).
4. Data Aggregation: Data is aggregated to produce daily, weekly, and monthly summaries.

2.3 Verification Process

The verification process shall consist of the following stages:

1. Pre-Verification Assessment: A preliminary review of the data collection and processing methodologies.
2. On-Site Verification: Physical verification of sensor installations and data collection practices.
3. Data Audit: A comprehensive audit of the data processing outputs against the original sensor data.

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3. Measurement Data

3.1 Data Formats

Data shall be reported in JSON format, which must adhere to the following schema:

`json { "project_id": "string", "sensor_id": "string", "timestamp": "ISO 8601 format", "measurement": { "co2": { "value": "float", "unit": "ppm" }, "ch4": { "value": "float", "unit": "ppm" }, "n2o": { "value": "float", "unit": "ppm" } }, "location": { "latitude": "float", "longitude": "float" }, "status": "string" } `

3.2 Data Field Mappings

The following data field mappings shall be established for reporting:

| Field Name | Description | Source | |-------------------|---------------------------------------------------------|----------------------------------| | project_id | Unique identifier for the carbon project | Assigned by Bureau Veritas | | sensor_id | Unique identifier for the sensor | DaedArch's internal ID | | timestamp | Date and time of measurement | ISO 8601 formatted string | | measurement.co2 | CO2 concentration measurement | Sensor output | | measurement.ch4 | CH4 concentration measurement | Sensor output | | measurement.n2o | N2O concentration measurement | Sensor output | | location.latitude| Latitude of the measurement location | Sensor GPS data | | location.longitude| Longitude of the measurement location | Sensor GPS data | | status | Status of the measurement (e.g., Valid, Invalid) | Derived from validation checks |

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4. Verification Findings

The verification findings shall include a detailed analysis of the data collected during the audit process. The following shall be reported:

• Data Integrity: Assessment of whether the data collected matches the expected values based on historical data and sensor calibration.
• Algorithm Performance: Evaluation of the certified algorithms used for data processing, including any deviations from expected performance metrics.
• Compliance with Standards: Confirmation that all data reporting conforms to the Bureau Veritas GHG inventory standards and CORSIA requirements.

4.1 Key Findings

• Data Integrity: The data collected from the sensors showed a 98% correlation with benchmark readings, indicating high reliability.
• Algorithm Performance: The algorithms demonstrated compliance with ISO 14064-3, with an accuracy rate of 95% as per the validation tests conducted.
• Compliance: All reporting formats and data fields were found to be compliant with Bureau Veritas standards, with no discrepancies noted.

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5. Conclusion

In conclusion, the verification of DaedArch Corporation's sensor-based MRV platform confirms that the data meets the necessary standards for GHG inventories and carbon project reporting. The thorough methodology employed ensures that the data collected is accurate, reliable, and compliant with both Bureau Veritas and CORSIA requirements.

5.1 Recommendations

• Continuous Monitoring: It is recommended that DaedArch implements ongoing monitoring of sensor performance and data accuracy to maintain compliance.
• Regular Audits: Periodic audits should be scheduled to ensure the ongoing integrity of the data collection and processing methodologies.
• Stakeholder Engagement: Engage with stakeholders to keep abreast of any changes in regulatory requirements that may impact the verification process.

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End of Document