Large Area Distributed Real Time Soil (DiRTS) Monitoring

大面积分布式实时土壤 (DiRTS) 监测

• 批准号: NE/T012331/1
• 负责人: Aleksandar Radu
• 金额: $ 49.97万
• 依托单位: Keele University
• 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%2FT012331%2F1
• 关键词: Large; Area; Distributed; Real; Time

Advancing our understanding of the soil ecosystem, especially the dynamics of nitrogen species, is critical for improving soil fertility, increasing crop productivity, managing greenhouse gas fluxes, and protecting environmental quality. This project presents convergent research to develop the next generation, integrated sensing system for large area, in situ, high resolution spatio-temporal monitoring of dynamic nitrogen species, specifically ammonium and nitrate, as well as soil moisture, potassium and salinity. The wireless Distributed Real Time Soil (DiRTS) monitoring network is comprised of (1) soil-penetrable sensor motes with advanced microfluidics mimicking plant root-like water intake, (2) robust electrochemical sensors for ammonium, nitrate, potassium and salinity utilizing ultra-low power circuit architectures for readout and digitization, (3) long range wireless data communication using emerging standards, and (4) advanced algorithms for geospatial mapping of soil mineral nitrogen, potassium, salinity and moisture. The platform will address fundamental weaknesses in our understanding and control of nitrogen species in both unmanaged (e.g. forest) and managed (e.g. agriculture) soils. Beyond the technical impact, the proposed research effort will offer educational and training opportunities for undergraduate and graduate students through innovative curriculum and for farmers and other soil management practitioners through publicly available training modules on design and deployment of the wireless Distributed Real Time Soil (DiRTS) monitoring platform.The DiRTS platform will make several notable scientific contributions: (1) Continuous capillary-driven sampling of the target soil nutrients mimicking the natural water intake by roots and transpiration through aboveground plant parts; (2) Ion sensitive electrodes utilizing embedded desalination to improve selectivity, and utilizing redundancy and Bayesian calibration to improve sensitivity; (3) Circuits for readout and digitization operating below 0.5V power supply and nanowatt level power dissipation; (4) Event-driven sampling and wireless communication using probabilistic sensor scheduling based on available power and data importance; and (5) State of the art statistical machine learning based approaches for generating high resolution spatio-temporal chemical maps from irregularly sampled data. All technology will be validated using actual, in-situ measurements of the target variable using the sensing mote and DET/DGT sensors in an experimental forest-BIFoR-FACE of the Birmingham Institute of Forest Research. Following validation, the sensing mote will then be fitted inside greenhouse gas auto-chambers in the FACE facility for concomittant sensing of dynamic nitrogen species and N2O fluxes to be monitored using a PICARO greenhouse gas analyzer and mapped using DiRTS sensor network. This proposal brings together experts in engineering, biogeosciences and chemistry from the US and UK, with strong backgrounds and expertise in relevant areas of sensing, electronics, microfluidics, biogeochemistry, soil science, signal processing and sensor networks, for successful execution of this project.

加深对土壤生态系统，特别是氮素物种动态的了解，对于改善土壤肥力、提高作物生产力、管理温室气体排放和保护环境质量至关重要。该项目旨在开发下一代集成传感系统，用于大面积、原位、高分辨率的动态氮素物种，特别是氨和硝酸盐，以及土壤水分、钾和盐分的时空监测。无线分布式实时土壤(DiRTS)监测网络包括：(1)可穿透土壤的传感器微粒，具有模拟植物根状水分吸收的先进微流体；(2)坚固的氨、硝酸盐、钾和盐度的电化学传感器，利用超低功率电路架构进行读出和数字化；(3)使用新兴标准的远程无线数据通信；以及(4)用于土壤矿物氮、钾、盐度和水分的地理空间制图的先进算法。该平台将解决我们在理解和控制未管理(例如森林)和管理(例如农业)土壤中的氮素物种方面的根本弱点。除了技术影响，拟议的研究工作将通过创新的课程为本科生和研究生提供教育和培训机会，并通过公开可用的关于设计和部署无线分布式实时土壤(DiRTS)平台的培训模块为农民和其他土壤管理从业者提供教育和培训机会。DiRTS平台将做出几个显著的科学贡献：(1)模拟植物地上部分的自然水分吸收和蒸腾作用的目标土壤养分的连续毛细管驱动采样；(2)离子敏感电极利用嵌入式脱盐来提高选择性，并利用冗余和贝叶斯校准来提高灵敏度；(3)低于0.5V电源和纳瓦级功耗的读出和数字化电路；(4)事件驱动采样和无线通信，使用基于可用功率和数据重要性的概率传感器调度；以及(5)基于最新统计机器学习的方法，用于从不规则采样数据生成高分辨率时空化学地图。所有技术都将通过使用传感微尘和DET/DGT传感器对目标变量进行现场实际测量来验证，这些传感器位于伯明翰森林研究所的实验森林BIFoR-Face中。验证后，感测微尘将安装在FACE设施的温室气体自动室内，用于伴随感测动态氮物种和N2O通量，使用Picaro温室气体分析仪进行监测，并使用DiRTS传感器网络绘制地图。这项建议汇集了来自美国和英国的工程、生物地理科学和化学专家，他们在传感、电子、微流体、生物地球化学、土壤科学、信号处理和传感器网络等相关领域具有丰富的背景和专业知识，以成功实施该项目。

项目成果

Portable, low-cost, Raspberry Pi-based optical sensor (PiSENS): continuous monitoring of atmospheric nitrogen dioxide

基于 Raspberry Pi 的便携式低成本光学传感器 (PiSENS)：连续监测大气二氧化氮

• DOI: 10.1039/d2ay01433e
• 发表时间: 2023
• 期刊: Analytical Methods
• 影响因子: 3.1
• 作者: Saiz, Ernesto;Banicevic, Ivana;Espinoza Torres, Sergio;Bertata, Salma;Picasso, Gino;O'Brien, Matthew;Radu, Aleksandar
• 通讯作者: Radu, Aleksandar

Performance modelling of zeolite-based potentiometric sensors

• DOI: 10.1016/j.snb.2021.131343
• 发表时间: 2022-01-05
• 期刊: SENSORS AND ACTUATORS B-CHEMICAL
• 影响因子: 8.4
• 作者: Jendrlin, Martin;Radu, Aleksandar;Kirsanov, Dmitry
• 通讯作者: Kirsanov, Dmitry

Stimulation of soil gross nitrogen transformations and nitrous oxide emission under Free air CO2 enrichment in a mature temperate oak forest at BIFoR-FACE

BIFoR-FACE 成熟温带橡树林在自由空气 CO2 富集下对土壤总氮转化和一氧化二氮排放的刺激

• DOI: 10.1016/j.soilbio.2023.109072
• 发表时间: 2023
• 期刊: Soil Biology and Biochemistry
• 影响因子: 9.7
• 作者: Sgouridis, Fotis;Reay, Michaela;Cotchim, Suparat;Ma, Jiaojiao;Radu, Aleksandar;Ullah, Sami
• 通讯作者: Ullah, Sami

Digital Colorimetry: Raspberry Pi-Based Sensors for Ar and Water Quality Monitoring

数字比色法：用于 Ar 和水质监测的基于 Raspberry Pi 的传感器

• DOI: 10.1149/ma2021-02551593mtgabs
• 发表时间: 2021
• 期刊: ECS Meeting Abstracts
• 作者: Radu A

A Pencil-Drawn Electronic Tongue for Environmental Applications.

• DOI: 10.3390/s21134471
• 发表时间: 2021-06-29
• 期刊: Sensors (Basel, Switzerland)
• 作者: Kirsanov D;Mukherjee S;Pal S;Ghosh K;Bhattacharyya N;Bandyopadhyay R;Jendrlin M;Radu A;Zholobenko V;Dehabadi M;Legin A
• 通讯作者: Legin A