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"sensitivity analysis" Keyword-tagged Publications:

Title Authors PubMed ID
1 Assessment of urban greenhouse gas emissions towards reduction planning and low-carbon city: a case study of Montreal, Canada Shadnoush Pashaei 38638449
ENCS
2 A DiffeRential Evolution Adaptive Metropolis (DREAM)-based inverse model for continuous release source identification in river pollution incidents: Quantitative evaluation and sensitivity analysis Zhu Y; Cao H; Gao Z; Chen Z; 38309421
ENCS
3 Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration Hou D; Zhan D; Wang L; Hassan IG; Sezer N; 37936825
ENCS
4 Development of a DREAM-based inverse model for multi-point source identification in river pollution incidents: Model testing and uncertainty analysis Zhu Y; Chen Z; 36191500
ENCS
5 Identification of point source emission in river pollution incidents based on Bayesian inference and genetic algorithm: Inverse modeling, sensitivity, and uncertainty analysis Zhu Y; Chen Z; Asif Z; 34380214
ENCS
6 Assessment of regional greenhouse gas emission from beef cattle production: A case study of Saskatchewan in Canada. Chen Z, An C, Fang H, Zhang Y, Zhou Z, Zhou Y, Zhao S 32217321
ENCS
7 Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction. Vorwerk J, Aydin Ü, Wolters CH, Butson CR 31231178
PERFORM

 

Title:Assessment of regional greenhouse gas emission from beef cattle production: A case study of Saskatchewan in Canada.
Authors:Chen ZAn CFang HZhang YZhou ZZhou YZhao S
Link:https://www.ncbi.nlm.nih.gov/pubmed/32217321?dopt=Abstract
DOI:10.1016/j.jenvman.2020.110443
Publication:Journal of environmental management
Keywords:Beef cattle productionClimate changeEmission assessmentGreenhouse gasMitigation measuresSensitivity analysis
PMID:32217321 Category:J Environ Manage Date Added:2020-03-29
Dept Affiliation: ENCS
1 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, H3G 1M8, Canada.
2 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, H3G 1M8, Canada. Electronic address: chunjiang.an@concordia.ca.
3 Faculty of Engineering and Applied Science, University of Regina, Regina, S4S 0A2, Canada.
4 Water Science and Environmental Engineering Research Center, College of Chemical and Environmental Engineering, Shenzhen University, Shenzhen, 518060, China.
5 School of Environmental Science and Engineering, Shandong University, Qingdao, 266237, China.

Description:

Assessment of regional greenhouse gas emission from beef cattle production: A case study of Saskatchewan in Canada.

J Environ Manage. 2020 Mar 25;264:110443

Authors: Chen Z, An C, Fang H, Zhang Y, Zhou Z, Zhou Y, Zhao S

Abstract

The beef cattle production has been considered as one of the largest sources of greenhouse gases (GHGs) emission. A large amount of GHGs including N2O and CH4 from enteric fermentation and manure are discharged to atmosphere during beef-production process. In addition, a substantial amount of GHGs is also emitted from many other related processes such as feed production, transportation, and energy consumption. In this study, an emission assessment model was developed to quantify the amount of regional GHGs produced from the beef cattle production process. A case study was conducted based on the beef production in Saskatchewan, Canada. The results demonstrated that the GHG emissions from the annual marketed beef cattle in Saskatchewan in 2014 were 8.52 × 109 kg CO2-eq in total and the cattle-source GHGs (enteric CH4, manure CH4, and manure N2O emission) accounted for more than 90% of the total emission. Sensitivity analysis showed that the most critical factors influencing the GHG emission included feedlot manure handling system, cattle diet, feed additives, maximum methane producing capacity (Bo), and climate (temperature, precipitation, and potential evapotranspiration). The potential impacts of climate change on GHG emission from beef cattle production in Saskatchewan were also investigated. An overall decrease in the GHG emission can be observed due to the climate change, which are 3.67%, 4.96%, and 6.63% for 2020-2039, 2040-2059, and 2060-2099, respectively.

PMID: 32217321 [PubMed - as supplied by publisher]





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