کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6536663 1420846 2018 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimating methane emissions from beef cattle in a feedlot using the eddy covariance technique and footprint analysis
ترجمه فارسی عنوان
برآورد انتشار گازهای گلخانه ای از گاو گوشتی در یک تابلوی خوراکی با استفاده از تکنیک کوواریانس چرخشی و تحلیل ردیابی
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
چکیده انگلیسی
Measurements of methane (CH4) emissions from cattle could provide invaluable data to reduce uncertainties in the global CH4 budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The eddy covariance (EC) technique has recently been applied as an alternative to measure CH4 emissions from livestock systems, but heterogeneities in the source area and fetch limitations impose challenges to EC measurements. The main objective of this study was to estimate CH4 emissions rates per pen surface (Fpens) and per animal (Fanimal) from a beef cattle feedlot using the EC technique combined with two footprint models: an analytical footprint model (KM01) and a parametrization of a Lagrangian dispersion model (FFP). Fluxes of CH4 were measured using a closed-path EC system in a commercial feedlot. The footprint models were used to investigate fetch requirements and to estimate Fpens and Fanimal. The aggregated footprint area predicted by KM01 was 5-6 times larger than FFP estimates. On average, Fpens was 8 (FFP) to 14% (KM01) higher than the raw EC flux, but differences between Fpens and EC flux varied substantially depending on the location and size of the flux footprint. The monthly average Fanimal, calculated using Fpens and the footprint weighed stocking density, ranged from 83 to 125 g animal−1 d−1 (KM01) and 75-114 g animal−1 d−1 (FFP). The emission values are consistent with the results from previous studies in feedlots. These results suggest that the EC technique can be combined with footprint analysis to estimate gas emissions from livestock systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agricultural and Forest Meteorology - Volume 258, 15 August 2018, Pages 18-28
نویسندگان
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