DOI: 10.3354/cr01394
Scopus记录号: 2-s2.0-84976384952
论文题名: Spatial variability of daytime CO 2 concentration with landscape structure across urbanization gradients, Shanghai, China
作者: Pan C. ; Zhu X. ; Wei N. ; Zhu X. ; She Q. ; Jia W. ; Liu M. ; Xiang W.
刊名: Climate Research
ISSN: 0936577X
出版年: 2016
卷: 69, 期: 2 起始页码: 107
结束页码: 116
语种: 英语
英文关键词: Mobile measurements
; Shanghai
; Underlying landscape structure
; Urban CO2
Scopus关键词: carbon cycle
; carbon dioxide
; concentration (composition)
; fossil fuel
; heterogeneity
; landscape structure
; permeability
; spatial variation
; spatiotemporal analysis
; suburban area
; urban atmosphere
; urbanization
; vegetation cover
; China
; Shanghai
英文摘要: Cities play an important role in the global carbon cycle. However, direct measurements of CO 2 concentration in urban environments are still very limited. Using Shanghai as a case study, this paper investigated the spatial pattern of atmospheric CO 2 concentration and its relationship with landscape structure across urbanization gradients. From March to April 2014, CO 2 concentrations were measured at 2 m above ground level with a near-infrared gas analyzer along 6 transects with a total length of 335 km. The results showed that the mean near-surface CO 2 concentration among the 6 transects was 445.8 ± 40.5 ppm. The average CO 2 concentration in the inner city was higher (55.1 ppm) than that in the suburban area. Also, CO 2 concentration showed a significant spatial heterogeneity, with the highest CO 2 concentration in the northwest and the lowest in the southeast, in accordance with the urbanization gradients. Further analysis indicated that the spatial variability of CO 2 concentration was mainly influenced by the urban landscape structure and depended largely on the percent of impervious surface cover (ISA) with a positive correlation and on the lower explanatory power for the percent of vegetation cover (Veg) with a negative correlation. This indicated that the trend in atmospheric CO 2 in urban areas was likely to depend more on fossil fuel emissions than on vegetation change. The study also found that the Pearson's correlation (R) between CO 2 concentration and ISA or Veg achieved its highest value when the buffer distance was 5 km, which could be described by the stepwise regression equation CO 2 = 0.99ISA-0.18Veg + 378.18 (R 2 = 0.44, p < 0.01). © 2016 Inter-Research. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116392
Appears in Collections: 气候减缓与适应
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Recommended Citation:
Pan C.,Zhu X.,Wei N.,et al. Spatial variability of daytime CO 2 concentration with landscape structure across urbanization gradients, Shanghai, China[J]. Climate Research,2016-01-01,69(2)