Atmospheric Measurement Techniques (Oct 2024)

Local and regional enhancements of CH<sub>4</sub>, CO, and CO<sub>2</sub> inferred from TCCON column measurements

  • K. Mottungan,
  • K. Mottungan,
  • C. Roychoudhury,
  • V. Brocchi,
  • V. Brocchi,
  • B. Gaubert,
  • W. Tang,
  • M. A. Mirrezaei,
  • J. McKinnon,
  • Y. Guo,
  • D. W. T. Griffith,
  • D. G. Feist,
  • D. G. Feist,
  • D. G. Feist,
  • I. Morino,
  • M. K. Sha,
  • M. K. Dubey,
  • M. De Mazière,
  • N. M. Deutscher,
  • P. O. Wennberg,
  • R. Sussmann,
  • R. Kivi,
  • T.-Y. Goo,
  • V. A. Velazco,
  • W. Wang,
  • A. F. Arellano Jr.,
  • A. F. Arellano Jr.

DOI
https://doi.org/10.5194/amt-17-5861-2024
Journal volume & issue
Vol. 17
pp. 5861 – 5885

Abstract

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In this study, we demonstrate the utility of available correlative measurements of carbon species to identify regional and local air mass characteristics as well as their associated source types. In particular, we combine different regression techniques and enhancement ratio algorithms with carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) total column abundance from 11 sites of the Total Carbon Column Observing Network (TCCON) to infer relative contributions of regional and local sources to each of these sites. The enhancement ratios provide a viable alternative to univariate measures of relationships between the trace gases that are insufficient in capturing source-type and transport signatures. Regional enhancements are estimated from the difference between bivariate regressions across a specific time window of observed total abundance of these species (BERr for bulk enhancement regression ratio) and inferred anomalies (AERr for anomaly enhancement regression ratio) associated with a site-specific background. Since BERr and AERr represent the bulk and local species enhancement ratio, respectively, its difference simply represents the site-specific regional component of these ratios. We can then compare these enhancements for CO2 and CH4 with CO to differentiate between combustion and non-combustion air masses. Our results show that while the regional and local influences in enhancements vary across sites, dominant characteristics are found to be consistent with previous studies over these sites and with bottom-up anthropogenic and fire emission inventories. The site in Pasadena shows a dominant local influence (> 60 %) across all species enhancement ratios, which appear to come from a mixture of biospheric and combustion activities. In contrast, Anmyeondo shows more regionally influenced (> 60 %) air masses associated with high-temperature and/or biofuel combustion activities. Ascension Island appears to only show a large regional influence (> 80 %) on CO / CO2 and CO / CH4, which is indicative of transported and combustion-related CO from the nearby African region, consistent with a sharp rise in column CO (3.51 ± 0.43 % ppb yr−1) at this site. These methods have important applications to source analysis using spaceborne column retrievals of these species.