解决生命周期评估中的时空变化问题:审查重点关注与农业相关的应用
Sofia Bahmutsky1, Nicole Bamber1, Vivek Arulnathan1
1Food Systems PRISM Laboratory, Charles E. Fipke Centre for Innovative Research, 3247 University Way, University of British Columbia, Kelowna, BC, Canada, V1V 1V7.
Journal of environmental management
|September 28, 2025
概括
农业生命周期评估 (LCA) 需要更好的区域数据. 本研究综合了农业LCA的时空空间变异的方法,为改善准确性和解决数据限制提供了一个框架.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 系统分析 系统分析
背景情况:
- 农业生命周期评估 (LCA) 经常使用国家数据,可能误导区域/地方环境影响.
- 土壤和气候的变化显著影响到农场层面的LCA准确性.
- 由于数据缺口和软件限制,实施区域化的LCA具有挑战性.
研究的目的:
- 系统地审查将时空变化纳入农业LCA的方法.
- 确定和评估区域化农业LCA的软件和技术.
- 为从业人员提供决策支持框架.
主要方法:
- 使用系统性审查和元分析 (PRISMA) 准则的首选报告项目进行系统性文献审查.
- 评估现有的方法来解决LCA的空间和时间变化.
- 识别和评估相关的软件和数据源.
主要成果:
- 地理信息系统 (GIS) 通过建模时空模式来提高LCA的准确性.
- Brightway2,Temporalis和OpenLCA是动态/区域化LCA的领先软件;Ecoinvent提供广泛的区域数据.
- 土地利用和土壤有机碳是空间时间LCA变化的关键因素.
结论:
- 区域化数据和更新的方法论对于准确的农业生命力评估至关重要.
- 提供了时空方法的系统综合和决策支持框架.
- 虽然详细的建模可以用于精准农业,但高度细粒度的空间差异化往往不需要整体准确性.
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