CO2 spatio-temporal analysis in the Iberian Peninsula

被引:2
|
作者
Perez, Isidro A. [1 ]
Luisa Sanchez, M. [1 ]
Angeles Garcia, M. [1 ]
Pardo, Nuria [1 ]
Fernandez-Duque, Beatriz [1 ]
机构
[1] Univ Valladolid, Fac Sci, Dept Appl Phys, Paseo Helen 7, E-47011 Valladolid, Spain
关键词
Gaussian kernel; Epanechnikov kernel; Nonparametric methods; CO2 growth rate; Annual cycle; Iberian Peninsula; CARBON-DIOXIDE CONCENTRATION; ATMOSPHERIC BOUNDARY-LAYER; TEMPORAL SCALES; VERTICAL-DISTRIBUTION; SPATIAL-DISTRIBUTION; NORTHERN PLATEAU; TROPOSPHERIC CO2; CH4; VARIABILITY; IMPACT;
D O I
10.1016/j.scitotenv.2019.05.492
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A comparison between monthly CO2 values calculated in the Iberian Peninsula and those measured during six years commencing on October 2010 in the centre of its upper plateau is presented. Gaussian and Epanechnikov kernels are used to calculate CO2 concentration and its growth rate in the study region from values at certain grid points. Slight spatial differences are obtained, revealing that both concentration and growth rate are nearly uniform in the region. However, some intervals were proposed that were represented by bands (strips), distributed meridionally for concentration and zonally for growth rate. Band borders were smoother for the Gaussian kernel than for the Epanechnikov kernel. In addition, the probability distribution function of concentration and growth rate were obtained with both kernels. Temporal analysis is carried out adding a linear evolution for growth rate and a sinusoidal function for the annual cycle. This revealed similar patterns for the region and at the grid point nearest to the measurement site, given by a sinusoidal function with nearly constant amplitude, providing satisfactory agreement. However, measurements showed great dispersion, with the concentration being around 7 ppm higher than for the region. Temporal evolution is characterised by a growth rate of 2.39 ppm yr(-1) and a sinusoidal function with an amplitude decrease of 0.25 ppm yr(-1). (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:322 / 331
页数:10
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