Zeeshan Parvez

and 11 more

The Cedars is an area in Northern California with a chain of highly alkaline springs resulting from CO2-charged meteorological water interacting with a peridotite body. Serpentinization resulting from this interaction at depth leads to the sequestration of various carbonate minerals into veins accompanied by a release of Ca2+ and OH- enriched water to the surface, creating an environment which promotes rapid precipitation of CaCO3 at surface springs. This environment enables us to apply the recently developed Δ47-Δ48 dual clumped isotope analysis to probe kinetic isotope effects (KIEs) and timescales of CO2 transformation in a region with the potential for geological CO2 sequestration. We analyzed CaCO3 recovered from various localities and identified significant kinetic fractionations associated with CO2 absorption in a majority of samples, characterized by enrichment in Δ47 values and depletion in Δ48 values relative to equilibrium. Surface floes exhibited the largest KIEs (ΔΔ­47: 0.163‰, ΔΔ­48: -0.761‰). Surface floe samples begin to precipitate out of solution within the first hour of CO2 absorption, and the dissolved inorganic carbon (DIC) pool requires a residence time of >100 hours to achieve isotopic equilibria. The Δ48/Δ47 slope of samples from the Cedars (-3.223±0.519; 1 SE) is within the range of published theoretical values designed to constrain CO2 hydrolysis-related kinetic fractionation (-1.724 to -8.330). The Δ47/δ18O slope (-0.009±0.001) and Δ47/δ13C slope (0.009±0.001) are roughly consistent with literature values reported from a peridotite in Oman of -0.006±0.002 and -0.005±0.002, respectively. The consistency of slopes in the multi-isotope space suggests the Δ47-Δ48 dual carbonate clumped isotope framework can be applied to study CO2-absorption processes in applied systems, including sites of interest for geological sequestration.
Carbonate clumped isotope thermometry (Δ_47) is a temperature proxy that is becoming more widely used in the geosciences. Most calibration studies have used ordinary least squares linear regressions or York models to describe the relationship between Δ_47 and temperature. However, Bayesian models have not yet been explored for clumped isotopes. There also has not yet been a comprehensive study assessing the performance of commonly used regression models in the field. Here, we use simulated datasets to compare the performance of seven regression models, three of which are new and fit using a Bayesian framework. While Bayesian and non-Bayesian ordinary least squares linear regression models show the best overall accuracy for calibrations, Bayesian models outperform other models in terms of precision, especially if datasets are sufficiently large (>50 data points). For temperature reconstructions where a given regression model is applied to predict temperature from Δ_47), Bayesian and non-Bayesian models show variable performance advantages depending on the the structure of errors in the calibration dataset. Overall, our analyses suggest that the advantages of using Bayesian models for calibrating and reconstructing temperatures using clumped isotope paleothermometry are realized through the use of large calibration datasets (>50 data points). When used with large datasets, Bayesian regressions are expected to substantially improve the accuracy and precision of (i) calibration parameter estimates and (ii) temperature reconstructions (e.g., typically improving precision by at least a factor of two). We implement our comparative framework into a new web-based interface, BayClump. This data tool should increase reproducibility by enabling access to the different Bayesian and non-Bayesian regression models. Finally, we utilize BayClump with three published datasets to examine precision and accuracy in regression parameters and reconstructed temperatures. We show that BayClump yields similarly accurate results to published studies. However, the use of BayClump generally produces temperature reconstructions with meaningful reductions in temperature uncertainty, as demonstrated through reanalysis of data from a Late Miocene hominoids site in Yunnan, China.

Barbara Goudsmit

and 19 more

Our current understanding of global mean near-surface (land and sea) air temperature (GMSAT) during the Cenozoic era relies on paleo-proxy estimates of deep-sea temperature combined with assumed relationships between global mean deep-sea temperature (GMDST), global mean sea-surface temperature (GMSST), and GMSAT. The validity of these assumptions is essential in our understanding of past climate states such as the Early Eocene Climate Optimum hothouse climate (EECO, 56–48 Ma). The EECO remains relevant today, because EECO-like CO2 levels are possible in the 22nd century under continued high CO2 emissions. We analyze the relationship between the three global temperature indicators for the EECO using 25 different millennia-long model simulations with varying CO2 levels from the Deep-Time Model Intercomparison Project (DeepMIP). The model simulations show limited spatial variability in deep-sea temperature, indicating that local temperature estimates can be regarded representative of GMDST. Linear regression analysis indicates that compared to GMSST, both GMDST and GMSAT respond more strongly to changes in atmospheric CO2 by factors of 1.18 and 1.17, respectively. Consequently, this model-based analysis validates the assumption that changes in GMDST can be used to estimate changes in GMSAT during the EECO. Paleo-proxies of GMDST, GMSST, and GMSAT during EECO show the best fit with model simulations having an atmospheric CO2 level of 1,680 ppm, which matches paleo-proxies of atmospheric CO2 during EECO. Similar analyses of other past climate states are needed to examine whether these results are robust throughout the Cenozoic, providing insight into the long-term future warming under various shared socioeconomic pathways.

Alexandrea Jay Arnold

and 24 more

Lacustrine, riverine, and spring carbonates are archives of terrestrial climate change and are extensively used to study paleoenvironments. Clumped isotope thermometry has been applied to freshwater carbonates to reconstruct temperatures, however, limited work has been done to evaluate comparative relationships between clumped isotopes and temperature in different types of modern freshwater carbonates. Therefore, in this study, we assemble an extensive calibration dataset with 135 samples of modern lacustrine, fluvial, and spring carbonates from 96 sites and constrain the relationship between independent observations of water temperature and the clumped isotopic composition of carbonates (denoted by Δ47). We restandardize and synthesize published data and report 159 new measurements of 25 samples. We derive a composite freshwater calibration and also evaluate differences in the Δ47-temperature dependence for different types of materials to examine whether material-specific calibrations may be justified. When material type is considered, there is a convergence of slopes between biological carbonates (freshwater gastropods and bivalves), micrite, biologically-mediated carbonates (microbialites and tufas), travertines, and other recently published syntheses, but statistically significant differences in intercepts between some materials, possibly due to seasonal biases, kinetic isotope effects, and/or varying degrees of biological influence. Δ47-based reconstructions of water δ18O generally yield values within 2‰ of measured water δ18O when using a material-specific calibration. We explore the implications of applying these new calibrations in reconstructing temperature in three case studies.

Brandon Hunter

and 4 more

Civil and environmental engineering research and development are essential in the efforts to assess, design, improve, and implement infrastructure. Engineering disciplines are vital to adequately identifying infrastructure problems, improving designs, developing new technologies, and ensuring safety. While engineering is effective in assessing and improving infrastructure in general, it is significantly less effective in conducting research and development to combat fundamental environmental injustices. There exists no tool to design, execute and evaluate engineering infrastructure research and development through an environmental justice framework, which is vital to realize Justice 40 Executive Order 14008, which aims to invest in climate-resilient infrastructure that is specifically allocated towards environmental justice initiatives for disenfranchised communities. In the absence of a framework, various sectors, whether it be the private sector, philanthropy, academia, or government, each conduct engineering research and development under different theories as to how to realize positive change. Not only are some common engineering theories of change ineffective at addressing fundamental injustices, but many aspects result in the further perpetuation of inequities. Engineering disciplines need to adopt an equitable framework through which to engage in environmental justice efforts. The work herein presents a theory of change framework that various sectors can use to improve the equity and effectiveness of engineering research and development of infrastructure. We assess common engineering theories of change practiced in the private sector, philanthropy, academia, and government, and provide analysis, critique, and recommendations as to how engineering processes can effectively realize Justice 40.