Application of a Common Methodology to Select in Situ CO2 Observations Representative of the Atmospheric Background to an Italian Collaborative Network

Pamela Trisolino,Tatiana Di Iorio,Andrea Lanza,Paolo Bonasoni,Paolo Cristofanelli,Francesco Monteleone,Daniela Heltai,Maurizio Busetto,Alcide Di Sarra,Luigi Caracciolo Di Torchiarolo,Salvatore Piacentino,Antonio Vocino,Francescopiero Calzolari,Damiano Sferlazzo,Francesco Apadula

doi:10.3390/atmos12020246

Abstract

We describe and implement a data selection algorithm aimed at identifying background atmospheric CO2 observations from in situ continuous measurements. Several selection criteria for detecting the background data have been developed and are currently used: the main objective of this work was to define a common methodology to extract the atmospheric background signal minimizing heterogeneities due to the use of different selection algorithms. The algorithm used in this study, (BaDS, Background Data Selection) was tested and optimized using data (from 2014 to 2018) from four Italian stations characterized by markedly different environmental conditions (i.e., mountain, coastal and marine): Plateau Rosa (PRS), Mt. Cimone (CMN), Capo Granitola (CGR) and Lampedusa (LMP). Their locations extend from the Alps to the central Mediterranean. The adopted algorithm proved to be effective in separating the local/regional from the background signal in the CO2 time series. About 6% of the data at LMP, 11% at PRS, 20–38% at CMN and 65% at CGR were identified as non-background. LMP and PRS can be used as reference sites for the central Mediterranean, while CMN and CGR were more impacted by regional sources and sinks. Finally, we discuss a possible application of BaDS screened data.

Highlights

The aim of this study is to evaluate the ability of the background data selection algorithm (BaDS) methodology in extracting the information related to the background variability from CO2 time series recorded at fixed monitoring stations with substantially different characteristics: mountain, coastal and marine sites
We assessed the capability of a data selection methodology (BaDS) for identifying the observations representative of the atmospheric background from the time series of near-surface CO2 at four permanent observatories in Italy from 2014 to 2018: Plateau Rosa, Mt
In addition to providing hints about the ability of BaDS in detecting background data, the systematic comparison of the CO2 dataset recorded at these observatories is relevant to investigate the dependence of the observed CO2 variability as a function of altitude and latitude in Italy

Summary

Introduction

While satellite observations and ground-based remote sensing measurements have gained importance in recent decades [2,3,4], global and regional networks of in situ GHG observations still largely represent the reference information for GHG monitoring, emission and variability studies [1,5,6]. These networks are characterized by significant efforts dedicated to the harmonization and increased comparability of GHG observations [7,8,9]. The selected data were used to: (a) calculate a running median on 504 h (21 days), and (b) calculate the average difference between consecutive hourly mean values (defined as the “S” parameter)

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Discussion

Conclusion