Daily patterns of CO2 in the lower atmosphere of a rural site

Abstract

This paper investigates patterns of daily evolutions of CO 2 in the lower atmosphere at a rural site over 2 years. The first part is devoted to observation analysis using a clustering procedure. However, direct application of the average-linkage method yielded undesirable results. In order to improve this procedure, data were previously processed using three smoothing procedures: the kernel smoothing method, the elliptical procedure, and the second-order cylindrical model. These procedures successfully revealed that clusters were based on daily concentration and range. However, the unequal distribution of frequencies in the clusters proved to be a noticeable disadvantage. Four alternative and simpler schemes for grouping observations were proposed in the second part of this paper. The first, comprising groups following fixed values of daily range and mean concentration, provided a sharp contrast between spring, with a marked daily cycle linked to the biological peak, and summer with a smooth daily cycle and low concentration when the biological minimum was reached. The second scheme is based on isopleth analysis and considers observation groups of similar frequencies following an increasing order of mean concentration and daily range. As a result, seasonal evolution was less marked. Straight lines were the borders for groups in the third scheme, which was similar and simpler than the second. The final scheme divided observations by means of equations of daily range as a quadratic function of daily concentration. The groups formed may be linked to seasons, with the group prevailing in summer presenting a noticeable daily range.

Influence of Wind Speed on CO2 and CH4 Concentrations at a Rural Site

“…Finally, the last part of this analysis considers the daily and annual cycles of CO 2 and CH 4 . Although these cycles have previously been described [18,19], their response to wind speed merits a detailed study. Two procedures, one parametric and another nonparametric, are used to smooth and investigate the two cycles.…”

Trend Assessment for a CO2 and CH4 Data Series in Northern Spain

“…According to de Haan [10], Lorimer was the first author to use the kernel method for atmospheric dispersion modelling of inert airborne contaminants [11]. Since then, many authors have employed this mathematical technique to atmospheric time series [9,12].…”

“…Cleveland [7] suggested local regression methods to obtain visual information from scatterplots [8]. Kernel smoothing functions are an extension of the locally weighted average method which has been widely used in atmospheric temporal series [9]. Moreover, kernel regression methods have successfully been used in different air pollution data.…”