Academic Journal
A novel approach to rapidly tracking whole-farm methane emissions
| Title: | A novel approach to rapidly tracking whole-farm methane emissions |
|---|---|
| Authors: | Huilin Chen, Katarina Vinković, Chu Sun, Wouter Peters, Arjan Hensen, Hugo Denier van der Gon, Margreet van Zanten, Pim van den Bulk, Ilona Velzeboer, Tim van der Zee |
| Source: | Environmental Research Letters, Vol 20, Iss 3, p 034016 (2025) |
| Publisher Information: | IOP Publishing, 2025. |
| Publication Year: | 2025 |
| Collection: | LCC:Environmental technology. Sanitary engineering LCC:Environmental sciences LCC:Science LCC:Physics |
| Subject Terms: | methane, emissions estimate, emission factors, dairy farm, atmospheric observations, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999 |
| More Details: | 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1748-9326 |
| Relation: | https://doaj.org/toc/1748-9326 |
| DOI: | 10.1088/1748-9326/adb1f6 |
| Access URL: | https://doaj.org/article/42bceef9e5bb42e09cef41ff92fa4229 |
| Accession Number: | edsdoj.42bceef9e5bb42e09cef41ff92fa4229 |
| Database: | Directory of Open Access Journals |
| ISSN: | 17489326 |
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| DOI: | 10.1088/1748-9326/adb1f6 |
| Published in: | Environmental Research Letters |
| Language: | English |