Near-infrared study of new embedded clusters in the Carina complex

We analyse the nature of a sample of stellar overdensities that we found projected on the Carina complex. This study is based on 2MASS photometry and involves the photometry decontamination of field stars, elaboration of intrinsic colour-magnitude diagrams J$\times$(J-Ks), colour-colour diagrams (J-H)$\times$(H-Ks) and radial density profiles, in order to determine the structure and the main astrophysical parameters of the best candidates. The verification of an overdensity as an embedded cluster requires a CMD consistent with a PMS content and MS stars, if any. From these results, we are able to verify if they are, in fact, embedded clusters. The results were, in general, rewarding: in a sample of 101 overdensities, the analysis provided 15 candidates, of which three were previously catalogued as clusters (CCCP-Cl$\,$16, Treasure Chest and FSR$\,$1555), and the 12 remaining are discoveries that provided significant results, with ages not above 4.5$\,$Myr and distances compatible with the studied complex. The resulting values for the differential reddening of most candidates were relatively high, confirming that these clusters are still (partially or fully) embedded in the surrounding gas and dust, as a rule within a shell. Histograms with the distribution of the masses, ages and distances were also produced, to give an overview of the results. We conclude that all the 12 newly found embedded clusters are related to the Carina complex.Comment: 10 pages, 14 figures, accepted for publication in MNRA

Large cities are less green

We study how urban quality evolves as a result of carbon dioxide emissions as urban agglomerations grow. We employ a bottom-up approach combining two unprecedented microscopic data on population and carbon dioxide emissions in the continental US. We first aggregate settlements that are close to each other into cities using the City Clustering Algorithm (CCA) defining cities beyond the administrative boundaries. Then, we use data on $\rm{CO}_2$ emissions at a fine geographic scale to determine the total emissions of each city. We find a superlinear scaling behavior, expressed by a power-law, between $\rm{CO}_2$ emissions and city population with average allometric exponent $\beta = 1.46$ across all cities in the US. This result suggests that the high productivity of large cities is done at the expense of a proportionally larger amount of emissions compared to small cities. Furthermore, our results are substantially different from those obtained by the standard administrative definition of cities, i.e. Metropolitan Statistical Area (MSA). Specifically, MSAs display isometric scaling emissions and we argue that this discrepancy is due to the overestimation of MSA areas. The results suggest that allometric studies based on administrative boundaries to define cities may suffer from endogeneity bias