DOI: 10.1016/j.atmosenv.2015.08.084
Scopus记录号: 2-s2.0-84941559008
论文题名: Semi-empirical process-based models for ammonia emissions from beef, swine, and poultry operations in the United States
作者: McQuilling A ; M ; , Adams P ; J
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 120 起始页码: 127
结束页码: 136
语种: 英语
英文关键词: Ammonia emissions
; Livestock production
; Manure management
; Process-based model
Scopus关键词: Agriculture
; Ammonia
; Animals
; Balloons
; Digital storage
; Errors
; Housing
; Manures
; Mass transfer
; Meats
; Ammonia emissions
; Livestock production
; Manure management
; Mass transfer resistances
; Measurement conditions
; Meteorological condition
; Nitrogen mass balance
; Process-based modeling
; Measurement errors
; ammonia
; nitrogen
; ammonia
; atmospheric modeling
; atmospheric pollution
; emission inventory
; empirical analysis
; farm
; management practice
; manure
; mass transfer
; meat
; model test
; nitrogen
; pig
; pollutant source
; poultry
; animal housing
; Article
; atmosphere
; beef cattle
; broiler
; dairy cattle
; farm emission model
; grazing
; lagoon
; measurement error
; meteorology
; nitrogen urine level
; nonhuman
; pig
; poultry
; priority journal
; United States
; volatilization
; United States
; Gallus gallus
; Suidae
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Farm-level ammonia emissions factors in the literature vary by an order of magnitude due to variations in manure management practices and meteorology, and it is essential to capture this variability in emission inventories used for atmospheric modeling. Loss of ammonia to the atmosphere is modeled here through a nitrogen mass balance with losses controlled by mass transfer resistance parameters, which vary with meteorological conditions and are tuned to match literature-reported emissions factors. Variations due to management practices are captured by having tuned parameters that are specific to each set of management practices. The resulting farm emissions models (FEMs) explain between 20% and 70% of the variability in published emissions factors and typically estimate emission factors within a factor of 2. The r2 values are: 0.53 for swine housing (0.67 for shallow-pit houses); 0.48 for swine storage; 0.29 for broiler chickens; 0.70 for layer chickens; and 0.21 for beef feedlots (0.36 for beef feedlots with more farm-specific input data). Mean fractional error was found to be 22-44% for beef feedlots, swine housing, and layer housing; fractional errors were greater for swine lagoons (90%) and broiler housing (69%). Unexplained variability and errors result from model limitations, measurement errors in reported emissions factors, and a lack of information about measurement conditions. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81514
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA, United States
Recommended Citation:
McQuilling A,M,, Adams P,et al. Semi-empirical process-based models for ammonia emissions from beef, swine, and poultry operations in the United States[J]. Atmospheric Environment,2015-01-01,120