Geoscience Data Journal (Oct 2024)

Detrital zircon U–Pb ages and Hf isotope analyses of modern and Quaternary sediments in China: A new dataset with preliminary analysis

  • Xiyun Chen,
  • Ping Wang,
  • Hongsen Xie,
  • Longchen Zhu,
  • Xia Liao,
  • Xinggong Kong

DOI
https://doi.org/10.1002/gdj3.193
Journal volume & issue
Vol. 11, no. 4
pp. 374 – 384

Abstract

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Abstract Developments of detrital zircon geochronology have resulted in an explosion of publications that report or discuss detrital zircon data. Combined detrital zircon U–Pb ages with Hf isotope analyses from modern and Quaternary sediments have been widely carried out with the aim of characterizing continental crustal evolution and tracing sediment provenance. Although several detrital zircon databases have compiled U–Pb and Hf data on global scale, the dataset of detrital zircon with a special focus on modern sediment has rarely been compiled. Here, we publish a new detrital zircon dataset of modern and Quaternary sediments in China with 59,535 U–Pb ages and 4,971 Hf isotope data, with detailed information of isotope ratios, ages, Th/U, etc. Four types of sediments have been classified according to sedimentary environments, including fluvial, marine, aeolian and alluvial sediments. Preliminary analysis is carried out on these compiled data to provide new insights into sedimentary provenance and crustal evolution in China. Eight age populations are identified corresponding to tectonic–thermal or magmatic events, including 2,300–2,700 Ma, 1,800–2,000 Ma, 700–1,000 Ma, 400–500 Ma, 200–300 Ma, 120–200 Ma, 80–120 Ma and < 60 Ma. Accompanying with quantitative comparison between sediments from various sedimentary environments, these U–Pb age distributions reveal the provenance link between “source” and “sink” in both exorheic and endorheic drainages. The compiled εHf(t) data reflect that the crustal history of China is apparently episodic, whose pattern is similar to that of global record. Further work will be implemented for database construction, including the integration of latest literatures, AI‐based data extraction and data aggregation.

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