Showing papers by "Valérie Daux published in 2023"
TL;DR: The DOCU-CLIM dataset as discussed by the authors contains 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime, and evaluated by formulating proxy forward models.
Abstract: Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies.
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TL;DR: In this article , a 2D-NMR analysis of a glucose derivative (diacetonide glucofuranose, DAGF) with a precision better than 1 mUr at each C-atom position is presented.
Abstract: Quantitative nuclear magnetic resonance (NMR) for isotopic measurements, known as irm-NMR (isotope ratio measured by NMR), is well suited for the quantitation of 13C-isotopomers in position-specific isotope analysis and thus for measuring the carbon isotope composition (δ13C, mUr) in C-atom positions. Irm-NMR has already been used with glucose after derivatization to study sugar metabolism in plants. However, up to now, irm-NMR has exploited a "single-pulse" sequence and requires a relatively large amount of material and long experimental time, precluding many applications with biological tissues or extracts. To reduce the required amount of sample, we investigated the use of 2D-NMR analysis. We adapted and optimized the NMR sequence so as to be able to analyze a small amount (10 mg) of a glucose derivative (diacetonide glucofuranose, DAGF) with a precision better than 1 mUr at each C-atom position. We also set up a method to correct raw data and express 13C abundance on the usual δ13C scale (δ-scale). In fact, due to the distortion associated with polarization transfer and spin manipulation during 2D-NMR analyses, raw 13C abundance is found to be on an unusual scale. This was compensated for by a correction factor obtained via comparative analysis of a reference material (commercial DAGF) using both previous (single-pulse) and new (2D) sequences. Glucose from different biological origins (CO2 assimilation metabolisms of plants, namely, C3, C4, and CAM) was analyzed with the two sequences and compared. Validation criteria such as selectivity, limit of quantification, precision, trueness, and robustness are discussed, including in the framework of green analytical chemistry.