Comparison of the regional CO<sub>2</sub> mole fraction filtering approaches at a WMO/GAW regional station in China

Abstract

Abstract. The identification of atmospheric CO 2 observation data which are minimally influenced by very local emissions/removals is essential for trend analysis, for the estimation of regional sources and sinks, and for the modeling of long-range transport of CO 2 . In this study, four approaches are used to filter the atmospheric CO 2 observation records from 2009 to 2011 at one World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) regional station (Lin'an, LAN) in China. The methods are based on the concentration of atmospheric black carbon (BC), on a statistical approach (robust extraction of baseline signal, REBS), on CH 4 as an auxiliary tracer (AUX), and on meteorological parameters (MET). All approaches do suitably well to capture the seasonal CO 2 cycle at LAN. Differences are observed in the average regional mole fractions with annual values in the REBS method at least 1.7 ± 0.2 ppm higher than the other methods. The BC method may underestimate the regional CO 2 mole fractions during the winter-spring period and should be treated with caution. The REBS method is a purely statistical method and it may also introduce errors on the regional CO 2 mole fraction evaluations, as the filtered trend may be influenced by the "noisy" raw data series. Although there are correlations between CH 4 and CO 2 mole fractions at LAN, the different source/sink regimes may introduce bias on the regional CO 2 estimation in the AUX method, typically in summer. Overall, the MET method seems to be the most favorable because it mainly focuses on the influence of potential local sources and sinks, and considers diurnal variations and meteorological conditions. Using the MET method, the annual growth rate of regional CO 2 at LAN is determined to be 3.1 ± 0.01 ppm yr −1 (standard error) from 2009 to 2011.

Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO<sub>2</sub> data and its application to European elevated mountain stations

“…Data selection methods can be categorized into meteorological, tracer, and statistical selection methods (Ruckstuhl et al, 2012;Fang et al, 2015). Meteorological data selection makes use of the meteorological information at the measurement sites, which provides valuable information about the surrounding environment as well as air mass transport (Carnuth and Trickl, 2000;Carnuth et al, 2002).…”

“…Meteorological data selection makes use of the meteorological information at the measurement sites, which provides valuable information about the surrounding environment as well as air mass transport (Carnuth and Trickl, 2000;Carnuth et al, 2002). Forrer et al (2000), Zellweger et al (2003), and Kaiser et al (2007) intensively studied the relationship between measured trace gases (such as O 3 , CO, and NO x ) and meteorological processes at Zugspitze, Jungfraujoch, Sonnblick, and Hohenpeissenberg. For CO 2 , the most common parameters applied in the literature are wind speed and wind direction.…”

“…Threshold limits of 300 ppb for CO and 2000 ppb for CH 4 were defined by Sirignano et al (2010) to perform a regional analysis of CO 2 data at Lutjewad (the Netherlands) and Mace Head (Ireland). Similar approaches with black carbon and CH 4 were performed by Fang et al (2015) at Lin'an (China). Moreover, Chambers et al (2016) applied a data selection technique to identify baseline air masses using atmospheric radon measurements at the stations Cape Grim (Australia), Mauna Loa (Hawaii, USA), and Jungfraujoch (Switzerland).…”

Adaptive Baseline Finder, a statistical data selection strategy to identify atmospheric CO<sub>2</sub> baseline levels and its application to European elevated mountain stations

“…Data selection starts with validated data and identifies in subsequent steps a final subset of the validated data set based on pre-defined criteria for a specific quality such as representativeness. With a particular focus on CO 2 in this 15 study, it is commonly accepted that data selection methods can be categorized into meteorological, tracer and statistical selection methods Fang et al, 2015).…”

“…Threshold limits of 300 ppb for CO and 2000 ppb for CH 4 were defined to filter the analyzed CO 2 data at Lutjewad (the Netherlands) and Mace Head (Ireland) by Sirignano et al (2010). Similar approaches with black carbon and CH 4 were performed by Fang et al (2015) at Lin'an (China). Chambers et al (2016) developed and applied a data selection technique to identify baseline air masses using atmospheric radon measurements at the stations Cape Grim (Australia), Mauna Loa 5 (USA) and Jungfraujoch.…”