How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?
How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?
复制标题
在估算奶牛生产的温室气体排放时，如何比较农场模型？
DOI：
10.1017/s175173111700338x
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Hutchings NJ
中科院分区：
文献类型：
--
作者：
Hutchings NJ
欧盟的《努力分担条例》（ESR）将要求到2030年，包括农业在内的未纳入欧洲排放交易计划的部门的温室气体排放量比2005年减少30%。这将需要估计农业，包括奶牛生产系统目前和未来的排放量。使用农场规模模型作为从农场到国家规模的第3级方法的一部分，提供了比IPCC（2006）第2级更全面和信息量更大的方法，但需要独立的质量控制。比较使用模型模拟一系列情景的结果，探索适当范围的生物物理和管理情况，可以通过提供一个框架来将模型结果置于背景中，从而支持这一进程。为了评估模型之间的差异和理解差异的过程，在由两种气候（凉/干和暖/湿）×两种土壤类型（桑迪和粘土）×两种饲喂系统（仅草和草/玉米）组成的析因设计中，计算了八种奶牛养殖情景下四种农场规模模型（DairyWise、FarmAC、HolosNor和SFARMMOD）的温室气体排放估计值。每头奶牛的产奶量，追随者：奶牛的比例，粪便管理系统，氮（N）施肥和土地面积标准化的所有方案，以关联的结果与模型结构和功能的差异。草和玉米的潜在产量和肥料和粪肥中有效氮的施用分别规定。在农场规模和大多数贡献源的温室气体排放量方面，模型之间存在显著差异，尽管源的大小排序没有差异。农场规模的温室气体排放量，平均超过四个模型，是每年10.6吨二氧化碳当量（CO2 e）/公顷，每年1.9吨CO2 e/公顷的范围。尽管在情景中指定了关键的生产特征，但在每公顷年产奶量和进口的氮肥和精饲料量方面，模型之间仍然存在显着差异。这是因为这些模型对生物物理反应和反馈机制的描述不同，管理功能内化的程度也不同。我们的结论是，比较不同的农场规模模型的结果时，适用于一系列的场景将建立信心，在实现ESR目标，证明进一步投资于开发更广泛的场景和软件工具。
The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.