Characterisation model approach for LCA to estimate land use impacts on pollinator abundance and illustrative characterisation factors

Characterisation model approach for LCA to estimate land use impacts on pollinator abundance and illustrative characterisation factors
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LCA 的表征模型方法,用于估计土地利用对传粉媒介丰度的影响和说明性表征因子

DOI:
10.1016/j.jclepro.2022.131043
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发表时间:
2022
影响因子:
11.1
通讯作者:
Alejandre E
Alejandre E
中科院分区:
环境科学与生态学1区
文献类型:
--
作者:
Alejandre E

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本研究提出了第一种方法,以确定相对土地利用对传粉昆虫丰度的影响,为生命周期评价(LCA)。传粉媒介对全球农作物产量做出了重要贡献,近年来,传粉媒介数量下降的证据引发了人们对土地利用等因素如何影响传粉媒介的担忧。我们的新方法评估土地利用对传粉昆虫丰度的影响,并提出了一个新的影响类别,是兼容的生命周期影响评估(LCIA)的当前框架。虽然系统的文献研究表明,存在多种模型,可以评估传粉者丰度的影响,他们的参数化过于复杂的LCA的应用。为此,提出了一种基于专家知识的简化方法。该方法的实际应用说明通过连接,和表征,相关的土地利用类型来自广泛使用的LCA数据库,ecoinvent。说明性的表征因素表明,土地利用类型之间的关键差异,可以通过所提出的方法反映。通过更大样本的传粉者丰度估计,并改进模型,如空间差异的考虑,进一步发展强大的表征因素,将有助于确定农业实践的影响LCA研究,有助于防止进一步传粉者丰度下降。
This study presents the first approach to characterise relative land use impacts on pollinator abundance for life cycle assessment (LCA). Pollinators make an essential contribution to global crop production and in recent years evidence of declines has raised concerns on how land use, among other factors, affects pollinators. Our novel method assesses land use impacts on pollinator abundance and proposes a new impact category that is compatible with the current framework of life cycle impact assessment (LCIA). While a systematic literature research showed the existence of multiple models that could assess pollinator abundance impacts, their parameterization is too complicated for applications in LCA. Therefore, a simplified method based on expert knowledge is presented. The practical application of the method is illustrated through the connection to, and characterisation of, relevant land use types derived from the widely used LCA database, ecoinvent. The illustrative characterisation factors demonstrate that key differences among land use types can be reflected through the proposed approach. Further development of robust characterisation factors through a larger sample of pollinator abundance estimates, and improvements to the model, such as considerations of spatial differentiation, will contribute to the identification of impacts of agricultural practices in LCA studies, helping prevent further pollinator abundance decline.
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