Livestock farming is the dominant source of atmospheric ammonia (NH3) in large parts of the world. However, its emissions remain difficult to quantify because of the complex and diverse nature of farms, and the technical and practical challenges involved in measuring NH3. Emission estimates from individual farms are traditionally obtained from in situ measurements, while regional to global distributions are provided by infrared satellite sounders. Airborne hyperspectral infrared imaging can be used to map NH3 over large areas (>10km2) and at high spatial resolution (<5m), therefore providing measurements at a scale between in situ and satellite data. During a joint ESA-NASA funded campaign in the summer of 2023 near Grosseto, Italy, a cattle farm and its surroundings were overflown by a research aircraft 69 times in five days. Airborne hyperspectral longwave infrared imagery was collected using the NASA-JPL Hyperspectral Thermal Emission Spectrometer (HyTES). We developed an efficient lookup table approach to derive NH3 abundances and associated uncertainties from the HyTES radiance data. The resulting distributions reveal a diversity of small and large NH3 plumes emanating from the farm. Lagoons and barns were identified as the main emission hotspots. From these distributions and with the help of a box model, total farm fluxes were estimated for each overflight. The emission fluxes range from 3 +/- 1 to 7 +/- 5 ghd(-1)h(-1) for the first three days, in line with emission factors reported by other studies. Much larger emissions are seen on the last two days, between 13 +/- 8 and 59 +/- 42ghd(-1)h(-1), likely caused by specific farm activities. Overall, this case study demonstrates that airborne hyperspectral infrared imaging is a valuable complement to existing methods for quantifying NH3 emissions at the farm scale.

Airborne measurements of agricultural ammonia emissions: A case study over a livestock farm in Grosseto, Italy

Lorenzo Genesio;Valerio Capecchi;
2026

Abstract

Livestock farming is the dominant source of atmospheric ammonia (NH3) in large parts of the world. However, its emissions remain difficult to quantify because of the complex and diverse nature of farms, and the technical and practical challenges involved in measuring NH3. Emission estimates from individual farms are traditionally obtained from in situ measurements, while regional to global distributions are provided by infrared satellite sounders. Airborne hyperspectral infrared imaging can be used to map NH3 over large areas (>10km2) and at high spatial resolution (<5m), therefore providing measurements at a scale between in situ and satellite data. During a joint ESA-NASA funded campaign in the summer of 2023 near Grosseto, Italy, a cattle farm and its surroundings were overflown by a research aircraft 69 times in five days. Airborne hyperspectral longwave infrared imagery was collected using the NASA-JPL Hyperspectral Thermal Emission Spectrometer (HyTES). We developed an efficient lookup table approach to derive NH3 abundances and associated uncertainties from the HyTES radiance data. The resulting distributions reveal a diversity of small and large NH3 plumes emanating from the farm. Lagoons and barns were identified as the main emission hotspots. From these distributions and with the help of a box model, total farm fluxes were estimated for each overflight. The emission fluxes range from 3 +/- 1 to 7 +/- 5 ghd(-1)h(-1) for the first three days, in line with emission factors reported by other studies. Much larger emissions are seen on the last two days, between 13 +/- 8 and 59 +/- 42ghd(-1)h(-1), likely caused by specific farm activities. Overall, this case study demonstrates that airborne hyperspectral infrared imaging is a valuable complement to existing methods for quantifying NH3 emissions at the farm scale.
2026
Istituto per la BioEconomia - IBE
Airborne hyperspectral measurements
Ammonia emission fluxes
Agriculture
Livestock farm
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Descrizione: Airborne measurements of agricultural ammonia emissions: A case study over a livestock farm in Grosseto, Italy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/572861
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