## 4 Discussion  
Simulating the biological DNA damage effects in the human body in the case of REI, utilizing MC methodologies, has proved to be a useful methodology to better understand the effects of environmental radiation exposure. MC methods are computational algorithms of high predictive accuracy and useful for modelling phenomena with significant uncertainty inputs. Thus, this is a powerful approach for confirming that, given the characteristics of the living matter and the medium, such as density, distance from the radiation source, radiation energy and geometry, as well as the kind of particles, effectively affect the photon transport path. The associated expected DNA damage levels (DSBs, SSBs) are usually accompanied by 5-10 times more non-DSB lesions, increasing the mutational potential even at low levels of radiation dose [31; 106].  
As expected, our results show that, for a given exposure time and \({}^{137}\)Cs surface activity, the absorbed dose decreases exponentially as a function of the height from the ground surface of the gamma-ray source. In the same way, the number of initial complex damage levels per cell decreased exponentially when the height increased and depended on the duration of the exposure and the source activity. It is obvious that a higher surface activity of \({}^{137}\)Cs can induce a greater number of DSBs and SSBs. It is worth noting that according to in vitro experiments on normal mammalian cells, 10-35 DSBs/cell and 200-1000 SSBs/cell are expected to occur with doses of 0.2-1 Gy, respectively [80; 107]. This means that if an individual has received such a dose, they would have a 1-3% increased risk of cancer as well [108]. Additionally, if the number of DSBs per cell is greater than 35 in any irradiated cell, this cell will have a dramatic risk increase of mutations, probably leading to apoptosis or cell death [109].  
Although we know that many of the DSB lesions induced to a cell after IR exposure can be repaired by endogenous mechanisms within 24 h, some of these lesions are difficult to repair, leading possibly to mutation or cell death [110]. What we really need in order to evaluate the damage induced to an individual after an IR exposure caused by a REI is a correlation between the absorbed dose and the DNA damage.  
This study has several limitations. In particular, in order to obtain a reliable cancer risk estimate for a specific cohort of people affected by a REI, there are more factors that have to be taken into consideration i.e., chemical factors (smoking, alcohol drinking, heterocyclic amine intake by overcooked meat, occupational contact with pesticides, herbicides and fertilizers), biological factors (medical history of hepatitis B, C and D) and genetic ones (hereditary abnormalities in DNA repair and cell cycle genes), together with the IR relevant magnitudes measured in the affected area [111]. Another issue is the fact that it is difficult to isolate only one physical component of the total radiation relevant to a REI that affects a certain geographic area, since there no specific non variable irradiation limits in time and space, and the radionuclides released by such incidents affect public health both individually and as a whole. The latter issue has been overcome in part, via the use of MC techniques, which are useful tools utilized for modelling phenomena with uncertainty inputs.