A novel approach to rapidly tracking whole-farm methane emissions

被引:0
|
作者
Chen, Huilin [1 ,2 ]
Vinkovic, Katarina [2 ]
Sun, Chu [1 ]
Peters, Wouter [2 ,3 ]
Hensen, Arjan [4 ]
van der Gon, Hugo Denier [4 ]
van Zanten, Margreet [3 ,5 ]
van den Bulk, Pim [4 ]
Velzeboer, Ilona [4 ]
van der Zee, Tim [5 ]
机构
[1] Nanjing Univ, Sch Atmospher Sci, Joint Int Res Lab Atmospher & Earth Syst Sci, Nanjing, Peoples R China
[2] Univ Groningen, Energy & Sustainabil Inst Groningen ESRIG, Ctr Isotope Res CIO, Groningen, Netherlands
[3] Wageningen Univ & Res Ctr, Meteorol & Air Qual, Wageningen, Netherlands
[4] Netherlands Org Appl Sci Res TNO, The Hague, Netherlands
[5] Natl Inst Publ Hlth & Environm RIVM, Bilthoven, Netherlands
来源
ENVIRONMENTAL RESEARCH LETTERS | 2025年 / 20卷 / 03期
基金
欧洲研究理事会;
关键词
methane; emissions estimate; emission factors; dairy farm; atmospheric observations; GREENHOUSE-GAS EMISSIONS; AMMONIA EMISSIONS; N2O EMISSIONS; DAIRY; CH4;
D O I
10.1088/1748-9326/adb1f6
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Enteric fermentation and manure from livestock farming are major sources of methane (CH4) 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 CH4 emissions from a large number of dairy cow farms in the Netherlands based on single-transect mobile van measurements of CH4 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 (R2: minimum 0.42, maximum 0.86) between the estimated CH4 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 CH4 emission factors (including both enteric fermentation and manure) for the four separate campaign days were estimated using the slope between the CH4 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 kgCH4/d/AU. From the dataset, averaged over each of the four campaign days, we derived an estimate of the whole-farm CH4 emission factor, with a 95% confidence interval of 0.47 [0.13-0.81] kgCH4/d/AU. Our results demonstrate that CH4 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.
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页数:16
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