Using liquid chromatography‐isotope ratio mass spectrometry to measure the δ¹³C of dissolved inorganic carbon photochemically produced from dissolved organic carbon

Abstract

Dissolved inorganic carbon (DIC) has long been recognized as the main identifiable product of dissolved organic carbon (DOC) photochemical remineralization. However, quantification of DIC photoproduction in natural waters has been hampered by low photoproduction rates (nM to μM h−1) relative to high DIC background concentrations (μM to mM). Here, we describe a novel method to determine the δ13C of photoproduced DIC in three southeastern US river water samples (Savannah, Altamaha, St. Marys) using liquid chromatography‐isotope ratio mass spectrometry (LC‐IRMS). Initial (< 4 h) DIC photoproduction rates were similar to those quantified using published methods that rely on extensive sample manipulation, but were 3.3 times higher than measured via the previous methods for prolonged exposures (> 14 h). Keeling plots indicated that the average δ13C value for photoproduced DIC (−33.3 ± 1.4‰) was depleted in 13C relative to bulk riverine DOC, consistent with the preferential photomineralization of lignin. This average was used with a simple isotope mass balance approach to calculate the concentration of photoproduced DIC. The LC‐IRMS measures δ13C‐DIC shifts (typically ± 0.01 to 0.1‰) more precisely than DIC concentration changes in the early stages of irradiation. Therefore, the combination of LC‐IRMS analysis and our simple mass balance approach provides a new, higher precision method to quantify initial rates of DIC photoproduction and associated photochemical efficiency (i.e., apparent quantum yield) spectra in aquatic systems without any sample manipulation. A full description, sensitivity analysis and recommendations for the method are presented.

Quantifying Photodegradation of Peatland‐Derived Dissolved Organic Carbon in the Coastal Ocean of Southeast Asia

“…For Exp 4 where multiple spectral treatments were applied, we fitted the parameters c and d simultaneously to describe the AQY spectrum (Equation ) following Powers et al. (2017). A weighted parameter optimization was applied (Johannessen & Miller, 2001; Rundel, 1983).…”

Low photolability of yedoma permafrost dissolved organic carbon

“…The current study did not seek to quantify real-world rates of photoreactions. To determine environmentally relevant rates, spectrally resolved irradiations and a careful accounting of wavelength specific absorbed photon doses are required to determine the apparent quantum yield spectra that are the starting point for photochemical models [Hu et al, 2002;Powers et al, 2016;Stubbins et al, 2011;Stubbins et al, 2006]. The current study was instead designed to determine the fraction of DOM that is susceptible to photodegradation (i.e., the photolabile fraction) under broadband simulated sunlight Stubbins et al, 2010].…”

Inter‐laboratory differences in the apparent quantum yield for the photochemical production of dissolved inorganic carbon in inland waters and implications for photochemical rate modeling

“…Furthermore, photoproduced DIC agreed during early stages of irradiation (< 2 h) between natural river water and water that had been acidified, DIC‐stripped, and rebuffered, but for one water sample that was irradiated for 14 h the DIC‐stripped treatment gave DIC photoproduction that was ca. three times lower than for the unamended treatment (Powers et al 2017b). Also, the mathematical fitting parameters for the DIC AQY spectra of three Swedish low‐DIC lakes did not differ between DIC‐stripped and non‐stripped water samples (Koehler et al 2016).…”

“…Until new methods become available that allow reliable, sensitive analysis of photoproduced DIC with minimal sample manipulation, we are limited by experimental methods that reduce DIC background and generate a DIC signal large enough to accurately quantify photo-oxidation by using high-intensity radiation of typically several hours duration. Recent methods based on stable carbon isotope changes in the sample DIC pool during irradiation experiments may help lower the detection limit of DOM photooxidation and overcome sample pretreatment (Wang et al 2009;Powers et al 2017aPowers et al , 2017b.…”