https://paglab.org/tag/ammonia/AmmoniaHugo Blox Builder (https://hugoblox.com)en-usWed, 01 Apr 2020 00:00:00 +0000https://paglab.org/media/logo_hu_32055a858e223df5.pnghttps://paglab.org/tag/ammonia/https://paglab.org/project/nh3-min/Wed, 01 Apr 2020 00:00:00 +0000https://paglab.org/project/nh3-min/<h2 id="overview">Overview</h2> <p><strong>NH3-Min</strong> is a national consortium project funded through the <strong>Landwirtschaftlichen Rentenbank</strong>, coordinated by the <strong>Thünen Institute for Climate-Smart Agriculture</strong>. The project quantifies and evaluates <strong>ammonia (NH₃) losses from synthetic nitrogen fertilizers</strong> and develops evidence-based mitigation measures, while simultaneously assessing <strong>nitrogen use efficiency (NUE)</strong> in arable crop production.</p> <p>Around 15% of agricultural NH₃ emissions in Germany originate from synthetic N fertilizers. The four fertilizer types investigated—<strong>urea, calcium ammonium nitrate (CAN), ammonium nitrate urea solution (UAN), and ammonium sulfate urea</strong>—together account for more than 85% of NH₃ emissions from synthetic N fertilizers applied in Germany. <strong>Winter wheat</strong> serves as the model crop across all experimental sites.</p> <h2 id="objectives">Objectives</h2> <ul> <li><strong>Quantify NH₃ emissions</strong> from different synthetic N fertilizer types and application systems across diverse German agro-climatic conditions.</li> <li><strong>Evaluate mitigation options</strong> including incorporation/injection techniques and urease inhibitors.</li> <li><strong>Derive site-differentiated NH₃ emission factors</strong> for synthetic N fertilizers under German production conditions.</li> <li><strong>Assess NUE</strong> of different synthetic N fertilizers and application strategies in field crop experiments.</li> <li><strong>Transfer knowledge</strong> to farmers, advisors, and policymakers.</li> </ul> <h2 id="research-questions">Research Questions</h2> <ul> <li>How large are NH₃ emissions following application of different synthetic N fertilizers?</li> <li>What are the site-differentiated NH₃ emission factors across Germany?</li> <li>How effectively can application techniques (e.g., incorporation, injection) or inhibitors (urease inhibitors) reduce NH₃ emissions?</li> <li>How do fertilizer-dependent NH₃ emissions affect yields, N uptake, and NUE in winter wheat?</li> </ul> <h2 id="project-partners">Project Partners</h2> <ul> <li>Thünen Institute for Climate-Smart Agriculture</li> <li>Technical University of Munich (TUM)</li> <li>Julius Kühn-Institut – Federal Research Centre for Cultivated Plants (JKI)</li> <li>KTBL – Association for Technology and Structures in Agriculture</li> <li>Christian-Albrechts-Universität Kiel</li> <li>Forschungszentrum Jülich</li> <li>Technische Universität Berlin</li> <li>Universität Hohenheim</li> <li>Bayerische Landesanstalt für Landwirtschaft (LfL)</li> <li>Ingenieurgemeinschaft für Landwirtschaft und Umwelt (IGLU)</li> <li>Landwirtschaftskammer Niedersachsen</li> <li>Stickstoffwerke Priesteritz (SKWP)</li> </ul> <p><strong>Duration:</strong> 01.2021 – 12.2024</p>https://paglab.org/project/greenwindows4_0/Tue, 01 Jan 2019 00:00:00 +0000https://paglab.org/project/greenwindows4_0/<h2 id="overview">Overview</h2> <p><strong>GreenWindows4_0</strong> is a research project funded by the <strong>Federal Ministry of Food and Agriculture (BMEL)</strong>, jointly led by <strong>Prof. Urs Schmidhalter</strong> and <strong>Prof. Kang Yu</strong> at the Technical University of Munich (TUM). The project develops precision tools and workflows for <strong>optimizing nitrogen (N) fertilization</strong> in arable farming, with the dual goal of reducing <strong>greenhouse gas (GHG) emissions</strong> (e.g., N₂O) and <strong>ammonia (NH₃) volatilization</strong> while maintaining crop productivity and N use efficiency.</p> <h2 id="objectives">Objectives</h2> <ul> <li><strong>Optimize N application timing and rates</strong> using satellite and UAV remote sensing to identify application windows that minimize emissions.</li> <li><strong>Monitor crop N status</strong> across field-scale experiments using hyperspectral and multispectral sensors.</li> <li><strong>Develop emissions-aware decision support</strong> linking remote sensing outputs to N management recommendations.</li> <li><strong>Improve N use efficiency (NUE)</strong> at the farm scale through data-driven approaches combining biophysical modelling and machine learning.</li> </ul> <h2 id="methodology">Methodology</h2> <p>The project integrates:</p> <ul> <li><strong>Satellite remote sensing</strong> (e.g., Sentinel-2) for large-area crop N status monitoring and yield estimation</li> <li><strong>UAV-based multispectral and hyperspectral imaging</strong> for high-resolution field phenotyping</li> <li><strong>Radiative transfer modelling</strong> and <strong>machine learning</strong> for robust trait retrieval</li> <li><strong>Field experiments</strong> with variable N fertilization treatments across multiple sites and seasons in Bavaria</li> </ul> <h2 id="project-partners">Project Partners</h2> <ul> <li><strong>Technical University of Munich (TUM)</strong></li> <li><strong>AGRAVIS NetFarming GmbH</strong></li> <li>Funded by: <strong>Federal Ministry of Food and Agriculture (BMEL)</strong></li> </ul> <p><strong>Duration:</strong> 01.01.2019 – 31.12.2022</p> <h2 id="related-publications">Related Publications</h2> <ul> <li>Mokhtari et al. (2025). <em>Satellite-based winter wheat yield estimation with a newly parameterized LUE model based on crop water status and leaf chlorophyll content.</em> <strong>Field Crops Research</strong>. <a href="../../publication/mokhtari-2025-fcr-satellitebased/">View</a></li> </ul>