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GB/T 46907-2025Technical specification for the data quality management of greenhouse gas emissions in industrial enterprises (English PDF)

工业企业温室气体排放数据质量管理技术规范

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Issued by

SAMR; SAC

Level / Type

National · Recommended

Issue date

December 31, 2025

Implementation date

July 1, 2026

Scope

GB/T 46907-2025 is the English-translated version of 工业企业温室气体排放数据质量管理技术规范.

GB/T 46907-2025 is the Chinese standard "Technical specification for the data quality management of greenhouse gas emissions in industrial enterprises".

Its scope clause reads: This document specifies the greenhouse gas data management and emission data acquisition technologies related to greenhouse gas emission data quality management for industrial enterprises.

Data acquisition, data quality management plan development, and data quality management plan improvement. This document applies to industrial enterprises conducting greenhouse gas emission data quality management. Its clauses include terms and definitions.

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Document preview — GB/T 46907-2025

National Standard of the People's Republic of China

ICS
13.020.10
Classification
Z 04

Issued by: State Administration for Market Regulation; Standardization Administration of the PRC

Contents

  • Preface
  • 1.Scope
  • 2 Normative References
  • 3.Terms and Definitions
  • 4 Greenhouse Gas Data Management
  • 5.Emissions Data Acquisition
  • 6.Development of a Data Quality Management Plan
  • Appendix A (Informative) Example 8 of Emissions Data Requirements for Data Quality Control Plan
  • Appendix B (Informative) Example of a Data Flow Activity Task List
  • Appendix C (Informative) Example 10 of Data Record Management
  • Appendix D (Informative) Example 11 of the Management of Measuring Instruments
  • References

1 Scope

This document specifies the greenhouse gas data management and emission data acquisition technologies related to greenhouse gas emission data quality management for industrial enterprises.

Data acquisition, data quality management plan development, and data quality management plan improvement.

This document applies to industrial enterprises conducting greenhouse gas emission data quality management.

2 Normative references

The contents of the following documents, through normative references within the text, constitute essential provisions of this document. Dated citations are listed below.

For references to documents, only the version corresponding to that date applies to this document; for undated references, the latest version (including all amendments) applies.

This document.

GB 17167 General Rules for the Configuration and Management of Energy Measuring Instruments in Energy-Using Units

GB/T 32150 General Rules for Greenhouse Gas Emission Accounting and Reporting by Industrial Enterprises

3 Terms and Definitions

The terms and definitions defined in GB/T 32150 and the following terms and definitions apply to this document.

3.1 Data quality management

To standardize data quality management and effectively improve data quality, industrial enterprises are implementing measures for acquiring emission data and managing data quality.

This involves a series of interconnected activities, such as the development of plans and the improvement of data quality management plans.

3.2 emission factor

A coefficient characterizing greenhouse gas emissions per unit of production or consumption activity.

Note. Data includes carbon dioxide emission factor, carbon content, oxidation rate, etc.

3.3 data source

Sources of data for greenhouse gas accounting.

Note. This includes the purchase quantity on the raw material settlement document, the amount of raw materials consumed on-site, and the lower heating value of fuel measured by the company itself.

3.4 data flow

Data quality management involves a series of workflows, including data monitoring, collection, statistics, accounting, and reporting.

3.5 data flow activity

The data flow involves specific tasks such as data recording, chemical analysis, fuel sampling, data aggregation, emission calculation, and storage.

3.6 Risk identification

The process of analyzing the possibility of omissions and errors in the data quality management process and classifying them according to the magnitude of the risk.

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This preview omits tables, figures, formulas and parts of the technical clauses. The complete document — 16 pages — is available in the English PDF.

Referenced standards

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