Precise measurement of 226Ra/230Th disequilibria in deep-sea sediments by high-sensitivity ICP-MS

Yuan, Liuting; Cai, Pinghe; Jiang, Xingyu; Geibert, Walter; Cheng, Yuehua; Chen, Yaojin

doi:10.1016/j.chemgeo.2023.121351

Cited by 6 publications

(4 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, a fraction of the adsorbed 226 Ra can be released into pore waters, via alpha recoil, diffusing into the overlying water column and/or it could be adsorbed by manganese oxides (Cochran & Krishnaswami, 1980). An estimated 70% of the total 226 Ra produced from decay of adsorbed 230 Th, is potentially exchangeable (Cochran & Krishnaswami, 1980; Yuan et al., 2023). Since sediment accumulation rates in the deep sea are on the order of mm/kyr (millimeters per millennium), sediment at depths of a few centimeters would represent at least 10,000 years—if burial was the main process.…”

Section: Resultsmentioning

confidence: 99%

“…This suggests that the increase in 210 Pb ex inventory was likely due to desorption and loss of 226 Ra from sediments. Some processes can interfere with the secular equilibrium of the 210 Pb– 226 Ra isotope pair, resulting in the reduction of 226 Ra ( K d < 500) and the preservation of 210 Pb ( K d = 10 4 –10 6 ) (Cochran & Krishnaswami, 1980; Yuan et al., 2023). Intense sediment reworking could induce such 226 Ra loss.…”

Section: Resultsmentioning

confidence: 99%

“…An important question is whether sediments release 226 Ra during disturbances, and if so, where does the 226 Ra go. Previous studies (Cochran & Krishnaswami, 1980;Kadko, 1980;Yuan et al, 2023) have shown that almost all the 226 Ra in deep-ocean sediment is generated from decay of its parent 230 Th. The isotope 230 Th is scavenged out of the water column and is adsorbed onto the surfaces of sediment particulate matter.…”

Section: Pb Ex Inventories Within the Smlmentioning

confidence: 99%

See 2 more Smart Citations

What Causes Excess Deepening of the Sediment Mixed Layer in the Deep Ocean?

Zhu,

Yu,

Bianchi

et al. 2024

Geophysical Research Letters

View full text Add to dashboard Cite

The sediment mixed layer (SML) in the deep ocean is an important interface with a rich diversity of benthic organisms. With increasing ocean mineral exploration, and eventual mining, the effect of sediment mixing on deep ocean ecosystems has raised considerable concern. We evaluate the distribution patterns and driving factors of SML depth in deep ocean nodule fields using naturally occurring 210Pb–226Ra isotopes. Results show that average SML depth has increased in Mn‐nodule fields since the end of the last century. SML processes are associated with significant desorption of 226Ra from sediments, resulting in a departure from radioactive equilibrium. By estimating possible driving factors, we conclude that anthropogenic exploration activities, rather than natural physical and/or biological drivers, are the most likely mechanism for intensified sediment mixing. 210Pb–226Ra disequilibria may be a potential tracer for quantifying the impact of human exploration on deep‐ocean sediment mixing and associated biological and geochemical effects.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Pb Ex Inventories Within the Smlmentioning

confidence: 99%

See 1 more Smart Citation

What Causes Excess Deepening of the Sediment Mixed Layer in the Deep Ocean?

Zhu,

Yu,

Bianchi

et al. 2024

Geophysical Research Letters

View full text Add to dashboard Cite

show abstract

“…The method can be applied to evaluate concentrations of radionuclide in many geothermal fields and excavation sites (Faruwa et al 2020;Cinelli et al 2020). It can also be used to decide the nature and uranium migration (UM) rate in many crustal formations (Youssef et al, 2017;Pereira and Ferreira, 2018;Reis et al 2020) (Yuan 2023), sedimentary surface identification for exploration of oil and gas, radioactive pollution discovery (Cinar et al 2017), mineral probing (Chandrasekaran et al 2014), pure earth science discoveries (Ray 2008;Sims 2021), facture and fissure unearthing linked with uranium concentrations elevation which is caused by uranium movement in fluid in the subsurface (Grozeva 2022) which can cause substantial problem for gamma-ray spectrometry investigation and explanation known as disequilibrium (Lefebvre 2022;Grozeva 2022;Cai 2015).…”

Section: Gamma Ray Spectrometry and Radioactive Series Disequilibriummentioning

confidence: 99%

Modification of Radiogenic Heat Production (RHP) Equation due to Radioactive Disequilibrium in Rock Samples from Gamma-Ray Spectrometry

Alabi,

Sedara,

Ajah

et al. 2023

Preprint

View full text Add to dashboard Cite

Many factors complicate the estimation of radiogenic heat production (RHP) which may lead to radionuclide concentrations which does not characterize the RHP being produced by rocks. One of this is the Uranium disequilibrium effect. We modified an existing model to minimize this effect. A revised data from gamma-ray spectrometry was used to compute the Beta and Alpha energies (Eβmax) of decay schemes, mass defect (EΔm)of radioelements, total absorbed energy (Eabs) per atom, numerical constants (Ai) and converted to the accepted RHP unit (µWm-3). The modified RHP model (A3) was evaluated and validated using error metrics and radiometric data from seven regions of Nigeria and India. The data was normalized to transform features to be on a similar scale to attain a normal distribution of the data. The modified model (A3) was compared with Birch’s (A1) and Rybach’s (A2) RHP models. All these processes were implemented in Python environment. The RHP constants is several percent higher (6.2% for U; 11.5% for Th) than the values of A1 and A2 RHP models except for Potassium which is higher (74.3%). The A3 RHP model gotten is: A(µWm-3) = ρ(0.103CU + 0.29CTh + 0.061CK). The contributing percentages of the radioelements were in the order of 40K > 238U > 232Th for the Southwest, Southeast and Northcentral regions of Nigeria while the order is 238U > 232Th > 40K for the Southsouth, Northeast and Northwest regions and in order 232Th > 238U > 40K for the Indian region. The A3 model returned a higher R2 value and lower SSE/RMSE/MAE values compared to A1 and A2 models. The R2 values ranged from 42–72% while RMSE ranged from 0.790–1.127. The A3 has the best performance in all metrics for all the regions. The coefficient of determination (R2) for the proportion of variance of the contribution of the radioelements placed K-40 as most dependent variable with a good correlation with the total RHP in the order of use of A1 < A2 < A3. In general A3 return the highest RHP values across all regions. The A3 RHP model gave a higher R2 value and lower RMSE, MAE, SSE values than A1 and A3 RHP models which is an indicator of best performance. The A3 RHP model performed well in all the regions in Nigeria and outside Nigeria. This shows that the A3 RHP model is not geological-formation dependent.

show abstract