The lithium and magnesium isotope signature of olivine dissolution in soil experiments
Introduction
Chemical weathering of continental silicate rocks supplies alkalinity and cations that drive carbonate formation and provides nutrients to the ocean to fuel primary productivity and organic carbon burial (Berner, 2003; Ebelmen, 1845). Because these are the primary processes removing CO2 from the atmosphere on timescales >105 years, weathering is a key process driving climate change over geologic time (Berner et al., 1983; Colbourn et al., 2015; Godderis et al., 2013). A climate-driven feedback may make silicate weathering a dominant climate-moderating process, helping to explain the long-term stability of Earth's climate (Walker et al., 1981). However, the strength of this feedback is disputed, in part because supply of weatherable material (high activity primary silicates) also exerts an important control on weathering fluxes (Goudie and Viles, 2012; Pogge von Strandmann et al., 2017a; Pogge von Strandmann et al., 2017c; Raymo et al., 1988; West et al., 2005).
Despite considerable research, the fundamental processes controlling weathering, and ultimately the evolution of atmospheric pCO2, are still poorly known. Understanding the relative roles of climate vs. material supply in determining weathering fluxes is challenging because the weathering mechanisms that operate at soil profile scales remain difficult to resolve. Moreover, it has proven difficult to relate soil-scale processes to those that operate at catchment and global scales, given the heterogeneities in supply of fresh primary rock, mineral saturation, pH, mineral surface area, reactivity and temperature in natural environments (e.g., Gislason et al., 2009; Maher and Chamberlain, 2014; Stallard and Edmond, 1983; Stefansson and Gislason, 2001; West et al., 2005). Laboratory experiments provide insight into mineral weathering rates and their dependence on many of these parameters, but rates calculated from laboratory experiments are generally several orders of magnitude higher than those observed in natural environments (White and Brantley, 2003), suggesting that the underlying mechanisms may also differ. To address this discrepancy, experiments emulating the inherently complex processes operating in the natural environment are necessary.
The uncertainty in understanding weathering rates in natural systems has further implications for understanding the potential for “enhanced weathering” as a strategy for removing anthropogenic CO2 from the atmosphere (Andrews and Taylor, 2019; Schuiling and Krijgsman, 2006; Taylor et al., 2015). Proposals for enhanced weathering include spreading finely-ground silicate and carbonate minerals on land surfaces (Hartmann et al., 2013; Koehler et al., 2010; Renforth, 2012; Schuiling and Krijgsman, 2006), in coastal environments (Hangx and Spiers, 2009; Schuiling and de Boer, 2010), and in the ocean (Koehler et al., 2013; Renforth et al., 2013). In each case, the aim is to increase the amount of mineral dissolution and associated CO2 drawdown. However, without precise knowledge of weathering rates, it is not yet possible to determine whether enhanced weathering would be a net sink of CO2, given the energy required for rock grinding and transportation (Moosdorf et al., 2014; Renforth, 2012).
A relatively new development in the study of weathering is the use of “non-traditional” stable isotopes. A number of these systems are fractionated by weathering processes and therefore have the potential to trace weathering, and even determine weathering fluxes. These tools could offer significant advantages over approaches that require several simultaneous measurements (e.g. multiple elemental concentrations, runoff rates, surface area, etc.). Magnesium isotopes (δ26Mg) are such a potential tracer of weathering processes, useful because Mg is a direct part of the long-term carbon cycle (Berner et al., 1983). Magnesium is present in both silicate and carbonate rocks, and these components typically have significantly different isotope ratios (Huang et al., 2013; Li et al., 2010; Saenger and Wang, 2014). This difference means that the δ26Mg of rivers is controlled both by lithology and by additional, smaller fractionation during uptake of mostly heavy Mg during formation of secondary minerals (Liu et al., 2014; Opfergelt et al., 2014; Opfergelt et al., 2012; Pogge von Strandmann et al., 2008; Pogge von Strandmann et al., 2012; Ryu et al., 2016; Tipper et al., 2010; Tipper et al., 2008; Tipper et al., 2006b; Wimpenny et al., 2011; Wimpenny et al., 2014).
Lithium isotopes (δ7Li) also show promise as an isotopic tracer of weathering, unusual in being dominantly controlled by silicate weathering. The Li isotope ratio is unaffected by plant uptake and primary productivity (Lemarchand et al., 2010; Pogge von Strandmann et al., 2016), and negligibly influenced by weathering of carbonates, even in carbonate-dominated catchments (Kisakürek et al., 2005; Millot et al., 2010; Pogge von Strandmann et al., 2017b). The δ7Li of silicate rocks comprises a narrow range (δ7Licontinental crust ~ 0.6 ± 0.6‰ (Sauzéat et al., 2015), δ7Libasalt ~ 3–5‰ (Elliott et al., 2006)) relative to that in rivers (2–43‰, global mean ~ 23‰ (Dellinger et al., 2015; Huh et al., 1998; Murphy et al., 2019; Pogge von Strandmann et al., 2006)). The high variability in rivers is caused by preferential uptake of 6Li into secondary minerals formed during weathering, driving residual waters isotopically heavy (Huh et al., 2001; Huh et al., 1998; Kisakürek et al., 2005; Lemarchand et al., 2010; Liu et al., 2015; Millot et al., 2010; Pistiner and Henderson 2003; Pogge von Strandmann et al., 2010; Pogge von Strandmann et al., 2006; Pogge von Strandmann and Henderson 2015; Pogge von Strandmann et al., 2014; Vigier et al., 2009; Wimpenny et al., 2015; Wimpenny et al., 2010). Dissolved Li isotope ratios are therefore controlled by the ratio of primary mineral dissolution (supplying low, rock-like, δ7Li to solution), relative to secondary mineral formation (preferentially removing 6Li and therefore leading to high dissolved δ7Li). This balance means that dissolved Li isotopes trace what is often referred to as the congruency of silicate weathering (where congruent weathering features a high ratio of primary mineral dissolution to secondary mineral formation) (Bouchez et al., 2013; Dellinger et al., 2015; Misra and Froelich, 2012; Pogge von Strandmann et al., 2010; Pogge von Strandmann and Henderson, 2015).
In this study, we examine Mg and Li isotope ratios from a well-characterised soil weathering experiment (Renforth et al., 2015). The aims of this study are (i) to better understand the processes that affect dissolved Li and Mg isotope compositions, (ii) to assess whether these isotopic tracers are useful for determining weathering processes and rates, including in enhanced weathering applications, and (iii) to compare isotopic methods with a more conventional approach to calculating weathering rates using elemental concentrations and ratios (Renforth et al., 2015).
Section snippets
Experimental approach
As a step towards bringing the inherently complex weathering environment into controlled laboratory conditions, 1 m long soil cores were taken from agricultural land. These cores are described in detail in Renforth et al., 2015. Briefly, three cores were extracted from the same location, in North Oxfordshire, UK. The bedrock in the region is Jurassic limestone and mudstone, and the soils are generally calcareous. The cores span the ploughed layer (~10 cm), the underlying B and C horizons, and
Methods
Major element concentrations in bulk soils and olivine powder were determined by XRF (Renforth et al., 2015). For isotope separation, material was dissolved in concentrated HF-HNO3-HClO4 at elevated temperature in PFA beakers on hotplates, followed by evaporation to dryness and sequential heated re-dissolution first in concentrated HNO3 and then in 6 M HCl. Exchangeable and carbonate fractions were also sampled using a sequential extraction technique (Tessier et al., 1979): the exchangeable
Mg isotopes
The MgO content of the olivine was 47.7 wt%, with a δ26Mg of −0.23 ± 0.06‰, identical to mantle-derived olivine (Pogge von Strandmann et al., 2011). In contrast, the bulk soils had around 0.50 ± 0.03 wt% MgO and a δ26Mg of −0.44‰ (Table 1). Around 0.5% of the initial bulk soil Mg was in the exchangeable fraction, based on the Na-acetate leach. Exchangeable Mg was isotopically light (−1.54 to −2.48‰; Fig. 2B). The carbonate fraction (comprising ~16% of the total soil Mg) was isotopically even
Magnesium
The mass balance of the effluent from the control core after 5 days from the start of the experiments shows that ~55% of the Mg stems from carbonate dissolution and ~ 42% from the exchangeable fraction (so these two sources make up >97% of the total eluted Mg) (Fig. 4). Less than 0.5% is initially from the dissolution of clay. By the end of the experiment, over 4 months later, the proportion from carbonate dissolution has increased to 65% at the expense of the contribution from the exchangeable
Conclusions
A well-characterised experiment in a soil core was used to assess the controls on lithium and magnesium isotope ratios during weathering. Olivine was added to the top of one core and compared to a control core without olivine.
For both Mg and Li, the exchangeable pool of sorbed elements on mineral surfaces in the soil exerted a significant role on the effluent composition, retarding the transport of chemical signals down the core by around 17–20 days. Ion exchange occurred in response to
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Isotope analyses and PPvS were funded by NERC advanced fellowship NE/I020571/2 and ERC Consolidator grant 682760 – CONTROLPASTCO2. PR and GMH acknowledge funding from the Oxford Martin School through the Oxford Geoengineering Programme, and from the Hay Family. Nicolas Boehm and Thomas Phelan (University of Oxford) are thanked for their help with experimental construction and sample collection, and Doug Hammond (USC) for discussion about data interpretation.
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