Ta1_P01

Radiocarbon dating of forensic human bone to estimate the postmortem interval (PMI)

Indra L¹, Hamann C², Szidat S³, Kanz F⁴, Lösch S¹, Lehn C⁵

¹Department of Physical Anthropology, Institute of Forensic Medicine, University of Bern, Bern, Switzerland, ²Leibniz-Laboratory for Radiometric Dating and Stable Isotope Research, Christian-Albrechts-Universität zu Kiel, Kiel, Germany, ³Department of Chemistry, Biochemistry and Pharmaceutical Sciences & Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland, ⁴Center for Forensic Medicine, Medical University of Vienna, Vienna, Austria, ⁵Institute of Legal Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany

Estimating the postmortem interval (PMI) of human remains is important in forensic anthropology, e.g. to aid the identification process. For this, a frequently employed method is radiocarbon dating, using the bomb-peak-model after 1950. Because of the bone remodeling, there is a lag time between the calibrated skeletal radiocarbon data and the actual year of death of an individual. The remodeling rate depends on the physiological state of the bone and may be different for each skeletal element. Quantifying these factors is challenging. By adding more data to this research field, our study aims to enhance the accuracy of radiocarbon-based PMI estimations of skeletal remains.

We radiocarbon-dated bone collagen from 25 forensic cases in Switzerland, Germany and Austria, of individuals that had died between 19 and 98 years of age. We sampled skull (occipital, parietal and temporal bone) and femur and combined the calibrated F¹⁴C values with the known individual data of the deceased to calculate collagen remodeling rates.

Our results show that petrous bone remodeling rates are low and lag times increasing roughly proportionate with age-at-death. The petrous bone is therefore less suitable for PMI estimation because its radiocarbon value refers to the period of the (early) childhood. Femur and skull remodeling rates are comparable. However, the inter-individual variability is pronounced, especially in the elderly. To create a universal model for year-of-death estimation based on the radiocarbon data, we need to better understand factors such as physiological status of the individual and its influence on skeletal turnover rates.