Harmonizing soil carbon simulation models, emission factors and direct measurements used in LCA of agricultural systems

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Agricultural Systems Pub Date : 2025-04-28 DOI:10.1016/j.agsy.2025.104361

Simone Pelaracci , Pietro Goglio , Simon Moakes , Marie Trydeman Knudsen , Klara Van Mierlo , Nina Adams , Fossey Maxime , Alberto Maresca , Manuel Romero-Huelva , Muhammad Ahmed Waqas , Laurence G. Smith , Frank Willem Oudshoorn , Thomas Nemecek , Camillo de Camillis , Giampiero Grossi , Ward Smith

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引用次数: 0

Abstract

CONTEXT

The increasing demand for animal products, coupled with the need to reduce greenhouse gas (GHG) emissions from livestock production, highlights the urgency for effective mitigation strategies for livestock systems, including the cropping systems. Soil organic carbon (SOC) sequestration, a crucial approach for reducing atmospheric GHG concentrations, is often underrepresented in Life Cycle Assessments (LCA) of agricultural systems, largely due to methodological challenges in accurately accounting for soil carbon dynamics.

OBJECTIVE

The objective of this study was to evaluate soil carbon simulation models, emission factors and direct measurements used in LCA, with the aim of developing a harmonized approach for including soil carbon change in agricultural LCAs. The goals were to: i) assess soil carbon simulation models, emissions factors and direct measurements used in LCAs of agricultural systems; ii) evaluate the strengths and weaknesses of these models; iii) provide recommendations for LCA practitioners; and iv) identify areas for future methodological improvements.

METHODS

A systematic review of soil carbon simulation models, emission factors and direct measurements used in LCAs of agricultural systems was conducted, obtaining 263 relevant articles from an initial pool of 29,151. In addition to direct measurements, fifteen soil carbon simulation models and three methods based on emission factors were identified and categorized into three tiers based on complexity and data requirements. A modified Delphi participatory process was used to evaluate each method against established criteria through expert workshops.

RESULTS AND CONCLUSIONS

The results showed an inverse relationship between applicability and accuracy of methods, making the choice of methodology critical to achieving high-quality LCA results. Recommendations emphasize selecting methods based on objectives and data availability, while being aware of the effect of the initial soil carbon level and the assessment time period when using soil carbon simulation models. In addition, this study identified current methodological challenges in assessing soil C dynamics in LCA of agricultural systems.

SIGNIFICANCE

This research provides a foundation for improving LCA practices and supports better decision-making in mitigating climate impacts of agricultural systems.

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协调农业系统LCA中土壤碳模拟模型、排放因子和直接测量

对动物产品的需求不断增加，再加上需要减少畜牧生产产生的温室气体排放，凸显了为包括种植系统在内的畜牧系统制定有效减缓战略的紧迫性。土壤有机碳（SOC）固存是降低大气温室气体浓度的关键方法，但在农业系统生命周期评估（LCA）中往往没有得到充分体现，这主要是由于在准确计算土壤碳动态方面存在方法上的挑战。本研究的目的是评估土壤碳模拟模型、土壤碳排放因子和土壤碳直接测量方法，旨在建立一种统一的方法，将土壤碳变化纳入农业土地生态系统。目标是：1)评估农业系统LCAs中使用的土壤碳模拟模型、排放因子和直接测量方法；Ii)评估这些模型的优缺点；iii)为LCA从业者提供建议；确定未来方法改进的领域。方法对农业系统LCAs中使用的土壤碳模拟模型、排放因子和直接测量方法进行系统综述，从29,151篇初始库中获得263篇相关文章。除直接测量外，还确定了15种土壤碳模拟模型和3种基于排放因子的方法，并根据复杂性和数据要求将其分为三个层次。通过专家研讨会，采用一种改进的德尔菲参与式过程，根据既定标准对每种方法进行评估。结果与结论方法的适用性与准确性呈反比关系，方法学的选择对获得高质量的LCA结果至关重要。建议强调基于目标和数据可用性选择方法，同时在使用土壤碳模拟模型时要意识到初始土壤碳水平和评估时间段的影响。此外，本研究确定了当前评估农业系统LCA土壤碳动态的方法挑战。意义本研究为改进LCA实践提供了基础，并为缓解农业系统气候影响提供了更好的决策支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Agricultural Systems 农林科学-农业综合

CiteScore

13.30

自引率

7.60%

发文量

174

审稿时长

30 days

期刊介绍： Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.