文章信息/Info

Title:

Data Model and Database Development for Chinese Materials Life Cycle Assessment

作者:

李小青; 龔先政; 聶祚仁; 王志宏

北京工業大學材料科學與工程學院

Author(s):

LI Xiaoqing; GONG Xianzheng; NIE Zuoren; WANG Zhihong

College of Materials Science and Engineering，Beijing University of Technology

關鍵詞:

環境負荷數據; 生命周期分析; 數據模型; 數據庫設計

DOI:

10.7502/j.issn.1674-3962.2016.03.02

文獻標志碼:

A

摘要:

作為數據密集型方法，高質量的數據是開展材料生命周期評價的重要前提，數據的可靠性直接影響著生命周期評價結果的可信度和應用性能。建設符合國情的材料生命周期環境負荷基礎數據庫，是我國開展LCA（Life Cycle Assessment）實踐的基礎數據保障和技術支撐。根據ISO14040系列國際標準關于LCA分析的基本框架，從技術領域、環境領域和價值領域分析了LCA實踐的數據要求和計算需求，建立了各領域實體的數據模型及清單數據的計算模型，完成了中國材料環境負荷數據庫（Sinocenter2.0）的總體框架設計和數據庫詳細設計，并對數據庫進行了兼容性分析；進一步簡要介紹了數據庫的主要內容，并在此基礎上開展了水泥能耗分析、材料生態設計等應用軟件開發，以及面向互聯網及大數據的LCA數據庫的應用研究；探討了材料環境負荷數據庫技術將來的主要研究內容和研究方向。

Abstract:

As the data intensive method, high quality environmental burden data is an important premise of carrying out materials life cycle assessment, and the reliability of data directly influences the reliability of the life cycle assessment results and its application performance. Therefore, building Chinese LCA database is the basic data needs and technical supports for carrying out and improving LCA practice. Firstly, according to requirement of ISO 14040 series standards, the data request and computation demand were studied from the scope of technique, environment and value fields, together with the detailed analysis and systemic abstract of LCA process, finally related models for LCA practice were developed. Based on the built models and the analysis of LCA database structure, functional assign and application demand, the general framework of Chinese LCA database named Sinocenter2.0 had been accomplished, the detailed design of database was also achieved, the compatibility of Sinocenter2.0 with the Ecoinvent database and ISO14048 standard is analyzed. Secondly, the main content of the database are briefly introduced, and the application software of cement energy consumption analysis and materials ecodesign were developed. Then the applied researches orient to Internet and big data technology were promoted. Finally, the future research works were proposed and discussed.