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Mondra - Hyper-modelled Scope 3 Carbon Accounting across Food Supply Chains

Mondra - Hyper-modelled Scope 3 Carbon Accounting across Food Supply Chains
Mondra - 跨食品供应链的超模型范围 3 碳核算
批准号:
830285
负责人:
金额:
$156.31万
依托单位:
依托单位国家:
英国
项目类别:
Innovation Loans
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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中文摘要
翻译
在该项目下,Mondra Global Limited寻求120万英镑的创新贷款资金用于实验开发(构建和真实世界试点),以提供改变游戏规则的解决方案,动态评估和减少全球食品供应链的碳排放。该解决方案利用自动化、机器学习和预测分析来推动整个系统的脱碳。业务需求:不断增加的碳监管迫使食品公司考虑90%的排放“被困”在产品供应链中。挑战:供应链信息(“范围3”)排放量无法获取或未知,这对数据共享和可追溯性构成重大障碍。做出净零承诺,包括范围3和与农民合作以提高绩效(英国零售商联盟,BRC-2020)。缺乏可扩展的解决方案来测量和监控“从源头到货架”的产品生态性能。最新技术:传统的碳建模是一种人工的、由顾问主导的活动,它将产品范围分解为成分量,并映射到旧的/过时的参考数据。每个产品需要数天/数周的时间,与实际情况的相似性有限,缺乏准确性和可操作的洞察力。针对供应链原始数据的更准确/更有洞察力的生命周期评估(LCA)方法通常由顾问主导,耗费大量精力,且成本高昂。与联盟合作伙伴合作,我们将提供Mondra Hyper-modeling,一个超可扩展的,为零售商/品牌所有者提供“即时可用”的供应链环境洞察服务。该解决方案直接使用来自30家零售商和250,000家供应商的大量预先验证的数据。数据包括食品成分/包装/供应链,下至农民/种植者。农业生态影响的评估采用先进的遥感/小面积估算技术,基于每年调查的35万农民的实地农场数据,这些数据是全球内插的,并通过卫星遥测进行验证。在原始数据不可用的情况下,Mondra ML缺口填充引擎完成树,并计算“源到架”的环境影响数字(温室气体排放/水资源短缺/富营养化/生物多样性),为零售商/品牌所有者提供消费“即服务”的见解/建议。商业级超级建模平台的实验开发和实际试点。与Oracle和我们的数据合作伙伴合作,蒙德拉屡获殊荣的管理团队拥有领导这一合作伙伴关系的经验,并得到了3 Keel(分包商)的支持,3 Keel是市场领先的可持续发展咨询公司,也是英国零售商联盟(BRC)NetZero 2040路线图的作者。
英文摘要
Under this project, Mondra Global Limited seeks £1.2M innovation loan funding for experimental development (build and real-world-pilot) to deliver a game-changing solution for dynamically assessing and reducing carbon emissions across global food supply chains. The solution leverages automation, machine-learning and predictive analytics to drive system-wide decarbonisation.Business need: Increasing carbon-regulation is forcing food corporations to consider the 90% of emissions "trapped" in product supply chains.Challenge: Information on supply-chain ("Scope 3") emissions is inaccessible or unknown, with major barriers to data sharing and traceability.Opportunity: Retailers making Net-Zero pledges that include scope-3 and collaboration with farmers to improve performance (British-Retail-Consortium, BRC-2020). Lacking a scalable solution for measuring and monitoring 'source to shelf' product eco-performance.Nearest-state-art: Traditional carbon modelling is a manual, consultant-led activity which breaks down product-ranges into ingredient volumes and maps to old/outdated reference-data. Takes days/weeks per product and bears limited resemblance to reality, lacks accuracy and actionable insight.A more accurate/insightful Life-Cycle-Assessment (LCA) approach which targets primary data from supply chains is typically consultant-led, laborious and prohibitively costly at scale.Game-changing solution - Mondra 'Hyper-modelling':Working with consortium partners, we will deliver Mondra Hyper-modelling, an ultra-scalable, 'instantly-available' supply chain environmental insights service for Retailers/Brand-owners.The solution directly consumes a wealth of pre-verified data from 30 Retailers and 250,000 suppliers. Data includes food product composition/packaging/supply-chain down to farmers/growers. Agricultural eco-impact is assessed using cutting-edge remote-sensing/small area estimation techniques based on 350K farmers surveyed annually for field-level farm data that is interpolated for the world and verified with satellite telemetry.Where primary data is unavailable, Mondra ML-gap filling engine completes the tree and 'source to shelf' environmental impact figures are calculated (GHG-emissions/water-scarcity/eutrophication/biodiversity), with insights/recommendations for Retailer/Brand owners to consume 'as-a-service'.Objectives & outputs: Experimental-development and real-world pilots for commercial-grade Hyper-modelling platform.Working with Oracle and our data partners, Mondra's award-winning management team has the experience to lead this partnership, supported by 3Keel (subcontractor), market-leading sustainability consultancy and authors of the British Retail Consortium (BRC) NetZero2040 roadmap.
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