A novel approach to rapidly tracking whole-farm methane emissions

Abstract Enteric fermentation and manure from livestock farming are major sources of methane (CH 4 ) emissions and have a large potential for emissions reduction. However, there is a lack of effective methods for evaluating future emissions reduction efforts, especially at the farm scale. We developed a rapid analysis method to evaluate CH 4 emissions from a large number of dairy cow farms in the Netherlands based on single-transect mobile van measurements of CH 4 concentrations downwind of farms located between 80 and 750 m from the road. Methane emissions from 51 dairy cow farms were determined on four campaign days within a total of 7 measurement hours between November 2017 and November 2018 using an inverse Gaussian approach combined with two different wind datasets and their composite. We found a range of moderate to high correlation ( R 2 : minimum 0.42, maximum 0.86) between the estimated CH 4 emission rates for 11–16 farms on each measurement day and the number of animal units (AUs, 1 AU equals 500 kg of animal weight) across four individual days. The whole-farm CH 4 emission factors (including both enteric fermentation and manure) for the four separate campaign days were estimated using the slope between the CH 4 emission rates derived from the composite of two distinct wind datasets and the number of AUs. Daily emission factors for the four campaign days were estimated to be in the range of 0.18–0.50 kgCH 4 /d/AU. From the dataset, averaged over each of the four campaign days, we derived an estimate of the whole-farm CH 4 emission factor, with a 95% confidence interval of 0.47 [0.13–0.81] kgCH 4 /d/AU. Our results demonstrate that CH 4 emissions from a large number of dairy cow farms can be rapidly estimated, providing an independent way to evaluate country-specific emission factors and a potential way to monitor future emission reductions.