We identify anthropogenic contributions to atmospheric CO2 measured at Mauna Loa using the statistical automatic model selection algorithm Autometrics. Estimating the determinants of atmospheric CO2 is traditionally a challenge due to the complex systems of data involved. CO2 is a highly autocorrelated, non-stationary time series, and globally there exist a large number of potential carbon sources and sinks. There is mixed evidence in the literature on anthropogenic contributions to atmospheric CO2: the long-term trend is widely attributed to human factors, while the main seasonal fluctuations are thought to be driven by the biosphere. However, the statistical measures applied are often somewhat unsatisfactory due to the complexities of dealing with large numbers of variables. Over the long run of geological time, evidence of repeated glaciations, and of coal and oil deposits from extinct tropical forests, reveals that atmospheric CO2 has varied greatly, and manifestly without any anthropogenic influence, including very low levels and levels as high as 1000 parts per million (ppm): see, for example, Hoffman and Schrag (2000); Hendry (2011) provides a summary. In the more recent half million years of ‘ice ages’, natural fluctuations include highs and lows of 300 and 180 ppm from Antarctic ice sheet drilling (see Juselius and Kaufmann, 2009). Finally, in the last 10 000–12 000 years, humanity has transformed planet Earth, replacing forests by agriculture and creating an industrial world (see, e.g., Ruddiman, 2005).
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