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Improving carbon footprinting of agricultural systems: Boundaries, tiers, and organic farming

2018; Elsevier BV; Volume: 71; Linguagem: Inglês

10.1016/j.eiar.2018.04.004

1873-6432

Cornelius Adewale, John P. Reganold, Stewart S. Higgins, R. Evans, Lynne Carpenter‐Boggs,

Soil Carbon and Nitrogen Dynamics

The purpose of this commentary is to call for consistent and improved methodology for agricultural carbon footprint (CF) studies. The methods of published agricultural CF studies were compared to identify areas of inconsistency. Organic agriculture has been proposed as an approach to reduce net agricultural greenhouse gas (GHG) emissions and sequester carbon. Therefore we used organic agriculture as a focal system to explore the impact on CF estimates of using inconsistent boundaries, soil emission accounting, and emission factor (EF) tiers. Studies of agricultural CF use inconsistent boundaries and most use EFs based on national averages or regional models. As a result the local and farm-to-farm variability of EFs are obscured and the comparability of CFs from different studies is dubious. We propose three principles for agricultural CF calculation: use of consistent broad agricultural system CF boundaries, incorporation of soil emissions and sequestration, and development and use of fine-scale EFs for agricultural inputs. The potential use of organic practices in GHG mitigation efforts, along with the annual inspection process for certified organic farms, justify the future use of organic farms as a longitudinal national or international study population using the proposed principles. Using different boundaries, or generalized vs. site-specific EFs, can give not only different levels of precision but also fundamentally different answers. Policy based on averaged data or incomplete estimates may be misdirected. To support effective policy and individual decision-making that reduce GHG emissions and/or sequester more carbon, accurate and consistent assessments of the GHG emissions of agricultural practices and systems at a finer temporal and spatial scale are needed.