Suppr超能文献

中国生命周期影响评价中大气 PM 导致健康损害的特征化因子本土化。

Indigenized Characterization Factors for Health Damage Due to Ambient PM in Life Cycle Impact Assessment in China.

机构信息

National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China.

Sustainable Development Research Center, Shandong University, Jinan 250061, China.

出版信息

Environ Sci Technol. 2024 Oct 1;58(39):17320-17333. doi: 10.1021/acs.est.3c08122. Epub 2024 Sep 19.

Abstract

Life cycle assessment (LCA) is a broadly used method for quantifying environmental impacts, and life cycle impact assessment (LCIA) is an important step as well as a major source of uncertainties in LCA. Characterization factors (CFs) are pivotal elements in LCIA models. In China, the health loss due to ambient PM is an important aspect of LCIA results, which, however, is generally assessed by adopting CFs developed by global models and there remains a need to integrate localized considerations and the latest information for more precise applications in China. In this study, we developed indigenized CFs for LCIA of health damage due to ambient PM in China by coupling the atmospheric chemical transport model GEOS-Chem, exposure-response model GEMM containing Chinese cohort studies, and the latest local data. Results show that CFs of four major PM precursors all exhibit significant interregional variation and monthly differences in China. Our results were generally an order of magnitude higher and show disparate spatial distribution compared to CFs currently in use, suggesting that the health damage due to ambient PM was underestimated in LCIA in China, and indigenized CFs need to be adopted for more accurate results in LCIA and LCA studies.

摘要

生命周期评价(LCA)是一种广泛用于量化环境影响的方法,而生命周期影响评价(LCIA)是 LCA 中的一个重要步骤,也是不确定性的主要来源之一。特征化因子(CFs)是 LCIA 模型中的关键要素。在中国,由于环境 PM 造成的健康损失是 LCIA 结果的一个重要方面,然而,这通常是通过采用全球模型开发的 CFs 进行评估的,因此仍需要整合本地化的考虑因素和最新信息,以便在中国更精确地应用。在这项研究中,我们通过耦合大气化学输送模型 GEOS-Chem、包含中国队列研究的暴露-反应模型 GEMM 以及最新的本地数据,为中国环境 PM 造成的健康损害的 LCIA 开发了本土化的 CFs。结果表明,在中国,四种主要 PM 前体的 CFs 均表现出显著的区域间差异和月度差异。与目前使用的 CFs 相比,我们的结果通常高出一个数量级,且呈现出不同的空间分布,这表明在中国的 LCIA 中,环境 PM 造成的健康损害被低估了,需要采用本土化的 CFs 以获得更准确的 LCIA 和 LCA 研究结果。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验