Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> CO<span class="inline-formula"><sub>2</sub></span> efflux at the water–air interface is an essential component of the riverine carbon cycle. However, the lack of spatially resolved CO<span class="inline-formula"><sub>2</sub></span> emission measurements prohibits reliable estimation of the global riverine CO<span class="inline-formula"><sub>2</sub></span> emissions. By deploying floating chambers, seasonal changes in river water CO<span class="inline-formula"><sub>2</sub></span> partial pressure (<span class="inline-formula"><i>p</i></span>CO<span class="inline-formula"><sub>2</sub></span>) and CO<span class="inline-formula"><sub>2</sub></span> emissions from the Dong River in south China were investigated. Spatial and temporal patterns of <span class="inline-formula"><i>p</i></span>CO<span class="inline-formula"><sub>2</sub></span> were mainly affected by terrestrial carbon inputs (i.e., organic and inorganic carbon) and in-stream metabolism, both of which varied due to different land cover, catchment topography, and seasonality of precipitation and temperature. Temperature-normalized gas transfer velocity (<span class="inline-formula"><i>k</i><sub>600</sub></span>) in small rivers was 8.29 <span class="inline-formula">±</span> 11.29 and 4.90 <span class="inline-formula">±</span> 3.82 m d<span class="inline-formula"><sup>−1</sup></span> for the wet season and dry season, respectively, which was nearly 70 % higher than that of large rivers (3.90 <span class="inline-formula">±</span> 5.55 m d<span class="inline-formula"><sup>−1</sup></span> during the wet season and 2.25 <span class="inline-formula">±</span> 1.61 m d<span class="inline-formula"><sup>−1</sup></span> during the dry season). A significant correlation was observed between <span class="inline-formula"><i>k</i><sub>600</sub></span> and flow velocity but not wind speed regardless of river size. Most of the surveyed rivers were a net CO<span class="inline-formula"><sub>2</sub></span> source while exhibiting substantial seasonal variations. The mean CO<span class="inline-formula"><sub>2</sub></span> flux was 300.1 and 264.2 mmol m<span class="inline-formula"><sup>−2</sup></span> d<span class="inline-formula"><sup>−1</sup></span> during the wet season for large and small rivers, respectively, 2-fold larger than that during the dry season. However, no significant difference in CO<span class="inline-formula"><sub>2</sub></span> flux was observed between small and large rivers. The absence of commonly observed higher CO<span class="inline-formula"><sub>2</sub></span> fluxes in small rivers could be associated with the depletion effect caused by abundant and consistent precipitation in this subtropical monsoon catchment.

Highlights

  • IntroductionRiver networks act as a processor that transfers and emits the carbon entering the water, rather than just 30 a passive pipe that transports carbon from the terrestrial ecosystem to the ocean (Cole et al, 2007; Battin et al, 2009; Drake et al, 2018)

  • CO2 efflux at the water–air interface is an essential component of the riverine carbon cycle

  • Lateral soil CO2 input and dilution effect caused by precipitation played critical roles in controlling riverine pCO2 in small rivers, while the decomposition of allochthonous organic carbon is responsible for pCO2 variability in large rivers

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Summary

Introduction

River networks act as a processor that transfers and emits the carbon entering the water, rather than just 30 a passive pipe that transports carbon from the terrestrial ecosystem to the ocean (Cole et al, 2007; Battin et al, 2009; Drake et al, 2018). Understanding the role that rivers play in the global carbon cycle is still hindered 35 by uncertainty on the estimate of CO2 flux outgassing from rivers (Cole et al, 2007; Raymond et al, 2013; Sawakuchi et al, 2017; Drake et al, 2018). Global riverine carbon emission estimates were largely based on data disproportionately focusing on temperate and boreal regions, including North America 45 and Europe (Raymond et al, 2013; Lauerwald et al, 2015; Drake et al, 2018). In light of this data gap, more studies are required in other data-poor regions to achieve a more accurate estimate

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