Assessment of CO2 emission rate from extended area sources with WindTrax model in a dairy cattle farm

This paper aimed to evaluate the WindTrax model to quantify CO2 (carbon dioxide) emissions in a commercial dairy cattle farm in Central Italy with a low-cost measurement system. A field trial of 20 minutes was conducted in February 2023, using two G-eko 2.0 MSPs (multi-sensor platforms), an anemometer, and a GNSS receiver, in unstable atmospheric conditions. Then, 5-minute averaged data were used as input in the WindTrax software for applying the backward Lagrangian Stochastic model. The model was used for calculating four mean CO2 emission rates (0.20212 ± 0.04994 g m-2 s-1) with 50,000 particles and the horizontal dispersion of CO2 concentrations around the sources using different numbers of particles (5,000, 10,000, 30,0000, and 50,000). Atmospheric dispersion maps, confidence interval concentration maps, and vertical profile plots were obtained by increasing the number of particles. The model shows better performances, in terms of confidence intervals, with a high number of particles with a stabilization of modeled median values between 30,000 and 50,000 particles. Horizontally, the lowest confidence intervals (near to zero) were obtained at 100–150 m from the sources along the wind direction, suggesting that the downwind sensor could be placed at a greater distance. Similarly, a better-defined vertical trend in modeled concentrations is observed as the number of particles increases. Wind gusts could have a great effect on emission rate calculation with limited sampling periods, as in this case, but simultaneously unstable atmospheric conditions affect the increased dispersion and dilution of CO2.