Radiocarbon concentration in tree-ring samples collected in the south-west Slovakia (1974-2013).

Appl Radiat Isot

Vienna Environmental Research Accelerator (VERA) Laboratory, Faculty of Physics, University of Vienna, 1090 Vienna, Austria.

Published: August 2017

Radiocarbon measurements of tree-ring samples collected in Vysoká pri Morave were compared with tree-ring data of the Žlkovce monitoring station situated 5km south-east from the Jaslovské Bohunice Nuclear Power Plant (NPP). Radiocarbon concentrations in Vysoká pri Morave and in Žlkovce tree rings were decreasing exponentially with decay constants of 14.48±1.23 y and 17.96±1.97 y, respectively, in agreement with similar results obtained at other radiocarbon stations. The Suess effect, represented by a dilution in C levels by fossil fuel CO emissions, was observed in both tree-ring data sets. The Vysoká pri Morave C data were during 1974-1995 systematically lower by about 50‰ than the Schauinsland (Germany) clean air reference values due to a regional fossil-fuel impact. However, after 1996 the Vysoká pri Morave C data were closer to the Schauinsland data due to lower CO emissions as a result of closing some of the heavy industry technologies in the region.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.apradiso.2016.12.001DOI Listing

Publication Analysis

Top Keywords

vysoká pri
16
pri morave
16
tree-ring samples
8
samples collected
8
tree-ring data
8
morave data
8
data
5
radiocarbon
4
radiocarbon concentration
4
tree-ring
4

Similar Publications

Treated municipal wastewater effluent is an important pathway for Contaminants of Emerging Concern (CEC) to enter aquatic ecosystems. As the aging wastewater infrastructure in many industrialized countries requires upgrades or replacement, assessing new treatment technologies in the context of CEC effects may provide additional support for science-based resource management. Here, we used three lines of evidence, analytical chemistry, fish exposure experiments, and fish and water microbiome analysis, to assess the effectiveness of membrane bioreactor treatment (MBR) to replace traditional activated sludge treatment.

View Article and Find Full Text PDF

This study aimed to explore the mechanisms underlying T-cell differentiation in asthma. Flow cytometry was performed to detect Th cells. LC-MS/MS was performed to assess lipid metabolism.

View Article and Find Full Text PDF

Purpose: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant opportunities in the diagnosis and management of glaucoma. This article explores the application of various DL models in enhancing OCT capabilities and addresses the challenges associated with their clinical implementation.

Methods: A review of articles utilizing DL models was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), autoencoders, and large language models (LLMs).

View Article and Find Full Text PDF

Since photosynthesis is highly sensitive to salinity stress, remote sensing of photosynthetic status is useful for detecting salinity stress during the selection and breeding of salinity-tolerant plants. To do so, photochemical reflectance index (PRI) is a potential measure to detect conversion of the xanthophyll cycle in photosystem II. Raphanus sativus var.

View Article and Find Full Text PDF

The cancers of the gastrointestinal (GI) tract have become a common diagnosis worldwide contributing to a large number of mortalities. Though potentially curable they are mostly fatal due to late diagnosis and lack of accurate diagnostic markers. microRNA, micromanagers of gene expression have been associated to have distinct roles as oncogenes or tumour suppressors in several cancers including GI cancers.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!