RT info:eu-repo/semantics/article
T1 Carbon dioxide at an unpolluted site analysed with the smoothing kernel method and skewed distributions
A1 Pérez Bartolomé, Isidro Alberto
A1 Sánchez Gómez, María Luisa
A1 García Pérez, María Ángeles
A1 Pardo Gómez, Nuria
K1 Rural CO2
K1 Kernel regression
K1 Distribution fitting
K1 Triangular distribution
AB CO2 concentrations recorded for two years using a Picarro G1301 analyser at a rural site were studied applyingtwo procedures. Firstly, the smoothing kernel method, which to date has been used with one linear andanother circular variable, was used with pairs of circular variables: wind direction, time of day, and time ofyear, providing that the daily cycle was the prevailing cyclical evolution and that the highest concentrationswere justified by the influence of one nearby city source, which was only revealed by directional analysis.Secondly, histograms were obtained, and these revealed most observations to be located between 380 and410 ppm, and that there was a sharp contrast during the year. Finally, histograms were fitted to 14 distributions,the best known using analytical procedures, and the remainder using numerical procedures. RMSE wasused as the goodness of fit indicator to compare and select distributions. Most functions provided similarRMSE values. However, the best fits were obtained using numerical procedures due to their greater flexibility,the triangular distribution being the simplest function of this kind. This distribution allowed us to identifydirections and months of noticeable CO2 input (SSE and April-May, respectively) as well as the daily cycleof the distribution symmetry. Among the functions whose parameters were calculated using an analyticalexpression, Erlang distributions provided satisfactory fits for monthly analysis, and gamma for the rest. Bycontrast, the Rayleigh and Weibull distributions gave the worst RMSE values.
PB Elsevier
SN 0048-9697
YR 2013
FD 2013
LK https://uvadoc.uva.es/handle/10324/65495
UL https://uvadoc.uva.es/handle/10324/65495
LA eng
NO Science of the Total Environment 456–457 (2013) 239–245
NO Producción Científica
DS UVaDOC
RD 28-nov-2024