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首页> 外文期刊>International Journal on Food System Dynamics >Measuring GHG Emissions Across the Agri‐Food Sector Value Chain: The Development of a Bioeconomy Input‐Output Model
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Measuring GHG Emissions Across the Agri‐Food Sector Value Chain: The Development of a Bioeconomy Input‐Output Model

机译:衡量农业食品部门价值链中的温室气体排放:生物经济投入产出模型的发展

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Increasing food production to meet rising global demand while minimising negative environmental impacts such as agricultural greenhouse gas (GHG) emissions is one of the greatest challenges facing the agri‐food sector. Sustainable food production relates not only to primary production, but also has wider value chain implications. An input‐output (IO) model is a modelling framework which contains information on the flow of goods and services across a value chain at a regional or national economy level. This paper provides a detailed description of the development of a Bioeconomy IO (BIO) model which is disaggregated across the subs‐sectors of the agri‐food value chain and environmentally extended (EE) to examine environmental outputs, including GHG emissions, We focus on Ireland, where emissions from agriculture comprise 33% of national GHG emissions and where there has been a major expansion and transformation in agriculture supported by national and EU policy. In a substantial Annex to this paper, we describe the modelling assumptions made in developing the BIO model. Breaking up the value chain into components, we find that most value is generated at the processing stage of the value chain, with greater processing value in more sophisticated value chains such as dairy processing. On the other hand, emissions are in general highest in primary production, albeit emissions from purchased animal feed are higher for poultry than for other value chains, given the lower animal based emissions from poultry than from cows or sheep. The level of disaggregation also shows that the sub‐sectors are themselves discrete value chains. The analysis highlights that emissions per unit of output are much higher for beef and sheep meat value chains than for pig and poultry. The analysis facilitated by the BIO model also allows for the mapping of emissions along the agri‐food value chain using the adapted IO EE approach. Such analysis is valuable in identifying emissions ‘hot‐spots’ along the value chains and analysing potential avenues for emission efficiencies.
机译:增加粮食产量以满足不断增长的全球需求,同时最大程度减少农业温室气体(GHG)排放等负面环境影响,是农业食品部门面临的最大挑战之一。可持续粮食生产不仅与初级生产有关,而且还具有更广泛的价值链含义。投入产出(IO)模型是一个建模框架,其中包含有关区域或国家经济水平上跨价值链的商品和服务流的信息。本文对生物经济IO(BIO)模型的开发进行了详细描述,该模型在农业食品价值链的各个子领域中进行了细分,并在环境扩展(EE)中进行了研究,以研究包括温室气体排放在内的环境产出。爱尔兰,其农业排放量占国家温室气体排放量的33%,并且在国家和欧盟政策的支持下,农业发生了大规模的扩张和转型。在本文的重要附件中,我们描述了在开发BIO模型时所做的建模假设。将价值链分解为各个组成部分,我们发现大多数价值是在价值链的加工阶段产生的,而在更复杂的价值链(如乳品加工)中具有更大的加工价值。另一方面,尽管家禽的动物性排放量比牛或绵羊低,但家禽的排放通常在初级产品中最高,尽管家禽的购买的动物饲料的排放量高于其他价值链。细分水平还表明,子行业本身是离散的价值链。分析强调,牛肉和绵羊肉价值链的单位产出排放量远高于猪和家禽。由BIO模型促进的分析还允许使用经过调整的IO EE方法在农业食品价值链上绘制排放量图。这种分析对于确定价值链中的排放“热点”并分析排放效率的潜在途径非常有用。

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