Air quality in schools is an important public health issue because children spend a considerable part of their daily life in classrooms. Particulate size and chemical composition has been associated with negative health effects. We studied levels of trace element concentrations in fine particulate matter (PM) in indoor versus outdoor school settings from six schools in Chañaral, a coastal city with a beach severely polluted with mine tailings. Concentrations of trace elements were measured on two consecutive days during the summer and winter of 2012 and 2013 and determined using X-ray fluorescence. Source apportionment and element enrichment were measured using principal components analysis and enrichment factors. Trace elements were higher in indoor school spaces, especially in classrooms compared with outdoor environments. The most abundant elements were Na, Cl, S, Ca, Fe, K, Mn, Ti, and Si, associated with earth's crust. Conversely, an extremely high enrichment factor was determined for Cu, Zn, Ni and Cr; heavy metals associated with systemic and carcinogenic risk effects, whose probably origin sources are industrial and mining activities. These results suggest that the main source of trace elements in PM from these school microenvironments is a mixture of dust contaminated with mine tailings and marine aerosols. Policymakers should prioritize environmental management changes to minimize further environmental damage and its direct impact on the health of children exposed.

No abstract

No abstract

This paper aims to identify typologies of Latin American cities based on socioeconomic urban environment patterns. We used census data from 371 urban agglomerations in 11 countries included in the SALURBAL project to identify socioeconomic typologies of cities in Latin America. Exploratory factor analysis was used to select a set of variables, and finite mixture modelling (FMM) was applied to identify clusters to define the typology of cities. Despite the heterogeneities among the Latin American cities, we also found similarities. By exploring intersections and contrasts among these clusters, it was possible to define five socioeconomic regional typology patterns. The main features of each one are low-education cities in Northeast Brazil; low-unemployment cities in Peru and Panama; high-education cities in Argentina, Chile, Colombia, Costa Rica, Nicaragua and Mexico; high female labor participation, with high primary education in Argentina and low primary education in Brazil; and low female labor participation and low education in Brazil, Colombia, El Salvador, Guatemala, and Mexico. Identifying clusters of cities with similar features underscores understanding of the urban social and economic development dynamics and assists in studying how urban features affect health, the environment, and sustainability.

Background: Environmental noise can cause auditory and non-auditory adverse effects. Aim: To identify daily environmental noise patterns in two urban sites of Metropolitan Santiago. Material and Methods: Continuous measurements of environmental noise in two sites of Metropolitan Santiago were analyzed by means of hierarchical cluster analysis. One site was a main street with heavy traffic and the second was a street from a neighborhood with intense nocturnal activity. The first phase of analysis consisted of clustering noise profiles with similar shapes according to the average linkage method, with correlation as the similarity measure. The second phase grouped the profiles with similar shapes into sub-clusters that also had similar absolute noise levels, using the complete linkage method, with absolute distance as the similarity measure. Results: Two noise patterns were identified for the first site, one for weekdays (Monday to Friday) and another for weekends (Saturday and Sunday). For the second site five different patterns were identified (Monday to Wednesday, Thursday, Friday, Saturday, and Sunday). Also different patterns appeared for summer compared to the rest of the year. The noise levels of both sites were high. Conclusions: The detected noise levels can be annoying, cause sleep disturbances and increase the risk for hypertension and cardiovascular diseases, among other effects.

No abstract

No abstract