DOI: 10.1016/j.atmosenv.2014.07.009
Scopus记录号: 2-s2.0-84904122993
论文题名: A regression approach for estimation of anthropogenic heat flux based on a bottom-up air pollutant emission database
作者: Lee S ; -H ; , McKeen S ; A ; , Sailor D ; J
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 95 起始页码: 629
结束页码: 633
语种: 英语
英文关键词: Anthropogenic heat
; Energy balance
; Urban heat islands
; Urban modeling
; Waste heat
Scopus关键词: Carbon monoxide
; Energy balance
; Energy utilization
; Nitrogen oxides
; Pollution
; Regression analysis
; Waste heat
; Anthropogenic heat
; Anthropogenic pollutants
; Energy consumption datum
; Mesoscale numerical model
; National emission inventories
; Statistical regression method
; Urban heat island
; Urban model
; Heat flux
; carbon monoxide
; nitrogen oxide
; air quality
; atmospheric pollution
; carbon monoxide
; database
; emission inventory
; energy balance
; heat flux
; heat island
; human activity
; nitrogen oxides
; numerical model
; regression analysis
; air pollutant
; air quality
; article
; bottom uo anthropogenic heat flux
; climate
; energy consumption
; land use
; mathematical parameters
; pollution and pollution related phenomena
; priority journal
; regression analysis
; suburban area
; Houston
; Texas
; United States
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: A statistical regression method is presented for estimating hourly anthropogenic heat flux (AHF) using an anthropogenic pollutant emission inventory for use in mesoscale meteorological and air-quality modeling. Based on bottom-up AHF estimated from detailed energy consumption data and anthropogenic pollutant emissions of carbon monoxide (CO) and nitrogen oxides (NOx) in the US National Emission Inventory year 2005 (NEI-2005), a robust regression relation between the AHF and the pollutant emissions is obtained for Houston. This relation is a combination of two power functions (Y=aXb) relating CO and NOx emissions to AHF, giving a determinant coefficient (R2) of 0.72. The AHF for Houston derived from the regression relation has high temporal (R=0.91) and spatial (R=0.83) correlations with the bottom-up AHF. Hourly AHF for the whole US in summer is estimated by applying the regression relation to the NEI-2005 summer pollutant emissions with a high spatial resolution of 4-km. The summer daily mean AHF range 10-40Wm-2 on a 4×4km2 grid scale with maximum heat fluxes of 50-140Wm-2 for major US cities. The AHFs derived from the regression relations between the bottom-up AHF and either CO or NOx emissions show a small difference of less than 5% (4.7Wm-2) in city-scale daily mean AHF, and similar R2 statistics, compared to results from their combination. Thus, emissions of either species can be used to estimate AHF in the US cities. An hourly AHF inventory at 4×4km2 resolution over the entire US based on the combined regression is derived and made publicly available for use in mesoscale numerical modeling. © 2014 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81092
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Atmospheric Science, Kongju National University, Gongju 314-701, South Korea; Chemical Sciences Division, NOAA Earth System Research Laboratory and University of Colorado/CIRES, Boulder, CO 80305, United States; Department of Mechanical and Materials Engineering, Portland State University, Portland, OR 97207, United States
Recommended Citation:
Lee S,-H,, McKeen S,et al. A regression approach for estimation of anthropogenic heat flux based on a bottom-up air pollutant emission database[J]. Atmospheric Environment,2014-01-01,95