A UAV-Based System for Validating a Backward Lagrangian Stochastic Model in a Dairy Cattle Farm

This study characterizes a compost-bedded pack barn of a dairy cattle farm in terms of CO<sub>2</sub> emissions approximately 20 min after tilling under stable atmospheric conditions. Emission fluxes were calculated with the bLS model WindTrax, assessing modeled CO<sub>2</sub> concentrations at two altitudes (5.0 m and 10.0 m ABGL) by comparing them with those measured by a UAV-based system at the same two altitudes. The UAV-based system was equipped with a low-cost self-engineered MSP (multi-sensor platform) containing an NDIR sensor for measuring concentrations and detecting environmental conditions, which were measured both by MSPs and commercial sensors. The input data were provided by the same sensors positioned on the ground (1.5 m ABGL), upwind and downwind with respect to the emission source. A sensitivity analysis of atmospheric stability in the bLS model yielded differences between median calculated emission fluxes for stable and unstable conditions from -0.020 to 0.034 g ∙ m<sup>-2</sup> ∙ s<sup>-1</sup>. Mean percentage errors gave overestimates of 8-39% and 13-21% 5.0 m and 10.0 m ABGL. The RMSE also indicated overestimates ranging from 44 to 275 ppm. This is the first study to validate concentrations calculated by a bLS model at two altitudes by using a UAV-based system on a compost-bedded pack barn.

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Journal
Sensors
Published
2025-11-03
DOI
https://doi.org/10.3390/s25216733
Primary Topic
Odor and Emission Control Technologies
Type
article
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article

A UAV-Based System for Validating a Backward Lagrangian Stochastic Model in a Dairy Cattle Farm

Jacqueline Cardoso Ferreira, Valentina Becciolini, Giuseppe Rossi, Gabriel Araújo e Silva Ferraz et al.
Sensors
Odor and Emission Control Technologies
article

A UAV-Based System for Validating a Backward Lagrangian Stochastic Model in a Dairy Cattle Farm

Jacqueline Cardoso Ferreira, Valentina Becciolini, Giuseppe Rossi, Gabriel Araújo e Silva Ferraz, Patrícia Ferreira Ponciano Ferraz, Leonardo Conti, Franck Morais de Oliveira, Arnaud de Mattia, Marco Merlini
article en

Abstract

This study characterizes a compost-bedded pack barn of a dairy cattle farm in terms of CO<sub>2</sub> emissions approximately 20 min after tilling under stable atmospheric conditions. Emission fluxes were calculated with the bLS model WindTrax, assessing modeled CO<sub>2</sub> concentrations at two altitudes (5.0 m and 10.0 m ABGL) by comparing them with those measured by a UAV-based system at the same two altitudes. The UAV-based system was equipped with a low-cost self-engineered MSP (multi-sensor platform) containing an NDIR sensor for measuring concentrations and detecting environmental conditions, which were measured both by MSPs and commercial sensors. The input data were provided by the same sensors positioned on the ground (1.5 m ABGL), upwind and downwind with respect to the emission source. A sensitivity analysis of atmospheric stability in the bLS model yielded differences between median calculated emission fluxes for stable and unstable conditions from -0.020 to 0.034 g ∙ m<sup>-2</sup> ∙ s<sup>-1</sup>. Mean percentage errors gave overestimates of 8-39% and 13-21% 5.0 m and 10.0 m ABGL. The RMSE also indicated overestimates ranging from 44 to 275 ppm. This is the first study to validate concentrations calculated by a bLS model at two altitudes by using a UAV-based system on a compost-bedded pack barn.

SensorsVol. 25(21)
Universidade Federal de Lavras (BR), University of Florence (IT)
Openalex Percentile: Top 75%
Odor and Emission Control Technologies
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