tokens: weak correlation of the slope with observed for the full sample is due to a second-order age effect, since the correlation of with age was negligible. We should also note that the sample plotted in the right panel of Fig. 10 consists of only 18 stars, which is less than the half of the whole sample, thus it suffers (more) from low number statistics. 7. Summary and conclusion To explore the effect of the star formation place (birthplace) on the chemical abundance trend with the condensation temperature, we selected a sample of main-sequence stars that have similar stellar parameters and expected similar ages as our Sun. The sample consisted of 39 stars, for 25 of which we carried out new observations with HARPS and UVES spectrographs. The spectra of the remaining 14 stars were taken from HARPS and UVES archives (ESO archive). We performed a detailed differential chemical abundance analysis and derived stellar ages for this sample of stars. When analysing the effect of the GCE on the [X/Fe] elemental ratios, we found that many elements display a strong dependence on stellar metallicity and most of the elements show a statistically significant trend with stellar ages. The latter result ([X/Fe] – age correlation) agrees well with that of Nissen (2015) . To minimize the GCE effect on trend that is due to time or age, we selected a sub-sample of stars that lie in a narrow range of ages from 2 to 4.5 Gyr. The stars were also selected to have errors on ages smaller than one Gyr. For this sub-sample of stars we found that the [X/Fe] abundance ratio of some elements correlates with the mean of the apo- and pericentric distances, . These Galactic radial abundance gradients qualitatively agree with those obtained from Cepheids (e.g. Lemasle et al. 2013 ) and from open clusters (e.g. Yong et al. 2012 ; Magrini et al. 2015 ). When considering only stars that are younger than 7 Gyr, we found no significant dependence of the trend on stellar age, as was observed in previous works (e.g. Adibekyan et al. 2014 ; Nissen 2015 ). As in Adibekyan et al. (2014) , when using the full sample of stars, we also observed some hint that the slope depends on , although not in a simple way. However, this dependence completely vanished when a sub-sample of stars with similar ages (the sub-sample mentioned in the previous paragraph) was considered. Here, we should note that this sub-sample consists of only 18 stars. With this small sample we still cannot firmly conclude whether the trend depends on the formation place of stars. A larger sample size and improvement in the data quality (higher S/N) as well as the use of very similar stars in terms of stellar properties (e.g. metallicity, temperature, age) that are observed at a wide range of Galactocentric distances will help to finally answer this question. In this context, the role of large surveys and missions, such as Gaia ( Perryman et al. 2001 ), Gaia -ESO ( Gilmore et al. 2012 ), and APOGEE ( Ahn et al. 2014 ), is
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