NSF Convergence Accelerator (L): Innovative approach to monitor methane emissions from livestock using an advanced gravimetric microsensor.

NSF Convergence Accelerator (L)：使用先进的重力微传感器监测牲畜甲烷排放的创新方法。

• 批准号: 2344426
• 负责人: Stephen Archer
• 金额: $ 65万
• 依托单位: Bigelow Laboratory for Ocean Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2344426&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Innovative; approach

The lifetime of methane in the atmosphere is relatively short compared to other major greenhouse gases; hence, reducing its emission represents a rapid option for slowing down global warming. Methane production from dairy and beef cattle is a considerable component of anthropogenic emissions and multiple on-farm strategies, including feed-additives, are being developed to reduce this source. The project aims to apply novel microsensor technology to quantify the emission of methane from individual cows. When linked to custom-designed information technology systems, this will allow estimation of methane emissions at the whole-herd scale. This will enable farmers to monitor and validate the effectiveness of methane-reduction approaches and provide the information required to access to carbon credit markets, an essential economic incentive for adoption of the emission-reduction approaches. Effective mitigation of methane emissions from agriculture, will benefit society as a whole by attenuating global warming.Through an expanding partnership of complementary expertise, the project aims to progress the development of a functional, robust, ear-tag mounted, methane microsensor that is sufficiently sensitive and selective to quantify concentrations in the vicinity of a cow’s muzzle, where most enteric methane is emitted. Preliminary trials on a working dairy farm are aimed at optimizing sensor deployment times, data recovery and interpretation strategies and to validate the measurements through intercomparison with established, scientific instrumentation. Additional partnerships will be established to design and implement data processing and interpretation systems that integrate with existing ‘smart agriculture’ technology. Initial engagement with experts in carbon accounting will be consolidated during the second phase of the project to establish methodologies that effectively utilize the microsensor technology as the basis for farm-specific emissions reduction quantification. The overarching goal is to transition an innovative microsensor technology from prototype to commercial readiness for application in the dairy and beef industries and integration in carbon credit market practices; with the intention that it will be an integral tool in the validation and promotion of mitigation strategies aimed at reducing enteric methane emissions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

与其他主要的温室气体相比，大气中甲烷的寿命相对较短。因此，减少其排放是减慢全球变暖的快速选择。乳制品和牛肉的甲烷生产是人为排放的考虑因素，并且正在开发多种农场策略，包括饲料吸附剂，以减少这种来源。该项目旨在应用新颖的微型传感器技术来量化单个母牛的甲烷排放。当与定制设计的信息技术系统链接时，这将允许在整个范围内估算甲烷排放。这将使农民能够监视和验证还原甲烷减少方法的有效性，并提供进入碳信贷市场所需的信息，这是采用减排方法的基本经济动机。有效缓解农业中的甲烷排放，将通过减轻全球变暖来使整个社会受益。通过扩大完善专业知识的伙伴关系，该项目旨在发展一个功能性，健壮，耳鸣的，甲烷微影响的发展，甲烷微电磁器足够敏感和选择性地量化了cow sectient op cow sectient op op op of op op of op op soper的浓度。对工作奶牛场的初步试验旨在优化传感器部署时间，数据恢复和解释策略，并通过与已建立的科学仪器进行比较来验证测量结果。将建立其他合作伙伴关系，以设计和实施与现有的“智能一致性”技术集成的数据处理和解释系统。在项目的第二阶段，将合并与碳会计专家的初步参与，以建立有效利用微传感器技术作为农场特异性排放量化定量的基础的方法。总体目标是将创新的微传感器技术从原型过渡到商业准备，以便在乳制品和牛肉行业的应用以及碳信贷市场实践中的整合；目的是它将成为旨在减少促进甲烷排放的缓解策略的验证和促进策略的组成工具。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的审查标准通过评估来通过评估来支持的。