Dynamic monitoring, reporting and verification for implementing negative emission strategies in managed ecosystems (RETINA)

在受管理的生态系统中实施负排放策略的动态监测、报告和验证（RETINA）

• 批准号: NE/V003240/1
• 负责人: Peter Smith
• 金额: $ 25.76万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV003240%2F1
• 关键词: Dynamic; monitoring; reporting; verification; implementing

Carbon sequestration in soil is one of the most promising biological negative emission (BNE) technologies to mitigate climate change. Soil carbon sequestration relies on the adoption of best management practices to increase the amount of carbon stored in soil. An advantage of soil carbon sequestration in agriculture is that carbon stocks are most depleted in cropland systems, so there is great potential to capture atmospheric carbon without land use conversion and competition for land resources. The successful implementation of land based negative emission technologies will require continuous monitoring, reporting and verification of soil storage changes and greenhouse gas (GHG) emissions to estimate net carbon sequestration in soils. Currently, a lack of cost effective, robust, consistent, transparent and accurate methods limits large-scale implementation of these technologies. Monitoring, reporting and verification of carbon sequestration and GHG emissions from soils could be achieved by combining information from novel cost-effective technological developments in field-based sensors, remote sensing, and/or smartphone apps and integration of models on cloud platforms to confirm management practice effectiveness. The process of detecting and inferring soil carbon changes and GHG emissions is extremely data intensive. In order to understand the variability in soil carbon and GHG emissions there is a need to combine information from diverse sensor networks in different environments and to accurately model soil carbon changes and GHG emissions from various management practices. Here we propose a cloud-based platform that combines new development in sensor-based technologies with cloud-based model simulations to overcome major obstacles for implementing a monitoring, reporting and verification (MRV) system for land based negative emission technologies. To operationalize the MRV system, we will collect and process sensor information from the field, land scape level sensors and national scale (Satellite data) and harmonize data feeds to cloud-based models. This setup allows near time simulations on carbon changes and GHG emissions on the cloud without the need for individual user inputs. This project offers the quality data and confidence required for visualising a future, rising to the demands of a net zero carbon UK by 2050. This project will undertake transdisciplinary research to harness recent advances in digital technology combined with novel approaches in stakeholder engagement to make a step change in delivering integrated management options, co-produced with stakeholders, which can help to mitigate climate change. There are several groups who will benefit from the outcomes of this research. We identify various stakeholders and interested groups; UK Farmers will benefit from a freely available mobile-App to help plan various management options to increase/maintain soil organic matter in soil while also accounting for GHG emissions from soil. For policy makers, web-based decision support tool developed in this project will forecast regional estimates of net soil carbon sequestration and GHG emissions. This project could help in designing strategies to monitor and improve environmental quality and reduce GHG emissions from managed ecosystems to meet net zero Britain by 2050. We anticipate wide interest from academia in the GHG budgets and various environmental data sources this project will generate. Keywords: Climate change, soils, carbon sequestration, Greenhouse gas emissions, cloud-based modelling

土壤固碳是缓解气候变化最有前景的生物负排放技术之一。土壤碳固存依赖于采用最佳管理做法来增加土壤中储存的碳量。土壤固碳在农业中的一个优势是农田系统中碳储量最耗尽，因此在不进行土地利用转换和争夺土地资源的情况下，捕获大气碳的潜力很大。陆基负排放技术的成功实施将需要持续监测、报告和核实土壤储存变化和温室气体(GHG)排放，以估计土壤的净固碳。目前，缺乏成本效益高、健壮、一致、透明和准确的方法限制了这些技术的大规模实施。监测、报告和核实土壤的碳固存和温室气体排放的方法是，将实地传感器、遥感和/或智能手机应用程序方面具有成本效益的新技术发展的信息结合起来，并在云平台上整合模型，以确认管理做法的有效性。探测和推断土壤碳变化和温室气体排放的过程是数据密集型的。为了了解土壤碳和温室气体排放的变异性，需要结合来自不同环境的不同传感器网络的信息，并准确地模拟土壤碳变化和来自各种管理做法的温室气体排放。在这里，我们提出了一个基于云的平台，将基于传感器的技术的新发展与基于云的模型模拟相结合，以克服实施陆基负排放技术监测、报告和验证(MRV)系统的主要障碍。为了实施MRV系统，我们将收集和处理来自实地、地貌水平传感器和国家比例尺(卫星数据)的传感器信息，并将数据馈送到基于云的模型。这种设置允许在云上对碳变化和温室气体排放进行近乎实时的模拟，而不需要单独的用户输入。该项目提供了展望未来所需的高质量数据和信心，满足了到2050年实现净零碳英国的要求。该项目将进行跨学科研究，以利用数字技术的最新进展，结合利益攸关方参与的新方法，在提供与利益攸关方共同制定的有助于缓解气候变化的综合管理备选方案方面做出一步改变。有几个群体将从这项研究的结果中受益。我们确定了不同的利益相关者和感兴趣的群体；英国农民将受益于一个免费可用的移动应用程序，以帮助规划各种管理选项，以增加/保持土壤中的土壤有机质，同时还考虑到土壤的温室气体排放。对于政策制定者，本项目开发的基于网络的决策支持工具将预测区域估计的土壤净碳汇和温室气体排放量。该项目可以帮助制定战略，监测和改善环境质量，减少受管理的生态系统的温室气体排放，以在2050年实现英国的净零排放。我们预计学术界将对该项目将产生的温室气体预算和各种环境数据来源产生广泛的兴趣。关键词：气候变化、土壤、碳固存、温室气体排放、基于云的模拟

项目成果

How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies.

• DOI: 10.1021/acs.est.2c02023
• 发表时间: 2022-09-20
• 期刊: ENVIRONMENTAL SCIENCE & TECHNOLOGY
• 影响因子: 11.4
• 作者: Albanito, Fabrizio;McBey, David;Harrison, Matthew;Smith, Pete;Ehrhardt, Fiona;Bhatia, Arti;Bellocchi, Gianni;Brilli, Lorenzo;Carozzi, Marco;Christie, Karen;Doltra, Jordi;Dorich, Christopher;Doro, Luca;Grace, Peter;Grant, Brian;Leonard, Joel;Liebig, Mark;Ludemann, Cameron;Martin, Raphael;Meier, Elizabeth;Meyer, Rachelle;Migliorati, Massimiliano De Antoni;Myrgiotis, Vasileios;Recous, Sylvie;Sandor, Renata;Snow, Val;Soussana, Jean-Francois;Smith, Ward N.;Fitton, Nuala
• 通讯作者: Fitton, Nuala

Ensemble machine learning for modeling greenhouse gas emissions at different time scales from irrigated paddy fields

• DOI: 10.1016/j.fcr.2023.108821
• 发表时间: 2023-03
• 期刊: Field Crops Research
• 影响因子: 5.8
• 作者: Zewei Jiang;Shihong Yang;Philip Smith;Qingqing Pang

Residual correlation and ensemble modelling to improve crop and grassland models

用于改进作物和草地模型的残差相关和集成建模

• DOI: 10.1016/j.envsoft.2023.105625
• 发表时间: 2023
• 期刊: Environmental Modelling & Software
• 影响因子: 4.9
• 作者: Sándor R

Evaluation of the DNDC Model to Estimate Soil Parameters, Crop Yield and Nitrous Oxide Emissions for Alternative Long-Term Multi-Cropping Systems in the North China Plain

• DOI: 10.3390/agronomy12010109
• 发表时间: 2022-01
• 期刊: Agronomy
• 作者: M. Abdalla;Xiao-Zong Song;X. Ju;Peter Smith

Agroecological Management and Increased Grain Legume Area Needed to Meet Nitrogen Reduction Targets for Greenhouse Gas Emissions

• DOI: 10.3390/nitrogen3030035
• 发表时间: 2022-09-01
• 期刊: NITROGEN
• 作者: Squire，Geoffrey R.;Young，Mark W.;Hawes，Cathy
• 通讯作者: Hawes，Cathy