T/JSAS 088-2025 Greenhouse gas—Quantification method and requirements for carbon footprint of products—Compound fertilizer (physical method)

Scope

This document specifies the purpose, scope of quantification, inventory analysis, impact assessment, interpretation of results, product carbon footprint report, and product carbon footprint declaration of the quantification of compound fertilizer (physical method) products. This document is applicable to the quantification of compound fertilizer (physical method) products. The quantification of other similar products can be referenced for use. 6.1.4 Data Quality Evaluation The purpose of data quality evaluation is to determine the credibility of the results and conclusions of carbon footprint quantification and to improve the key factors of data quality. In this document, data quality can be controlled and evaluated from four aspects, namely, time representativeness, geographical representativeness, technical representativeness, and accuracy. The formula for calculating the Data Quality Rating (DQR) is as follows: (1) where: — The score of the data in the dimension of time representativeness: — The score of the data in the dimension of technical representativeness: — The score of the data in the dimension of geographical representativeness: — The score of the data in the dimension of accuracy. The explanation and evaluation of the Data Quality Rating (DQR) are detailed in Tables 3 and 4. Table 3 Explanation of the Data Quality Rating (DQR) Score 1 The reference year of the carbon footprint is within the validity period of the secondary database. The technical methods involved in the background data set are the same as those involved in this study. The location of carbon footprint calculation belongs to the same geographical region (region/province/city/state, etc.) as the source of the background data set. Raw data obtained through on-site investigation or measurement 2 The reference year of the carbon footprint exceeds the validity period of the secondary database by ≤2 years. The technical combination involved in the background data set includes

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