Relationship Between Pollution Levels and Socioeconomic Variables: Conditions in Nine Regional Municipalities in Valparaíso, Chile

Abstract

Air pollution, which generates negative effects on people's health, is linked to 23% of deaths worldwide. Among the main air pollutants are particulate matter (PM10 and PM2.5), which causes cardiovascular and respiratory diseases, affecting the whole community living in a sector exposed to emissions; and sulphur dioxide (SO2), which can cause severe effects even with short exposures. Based on air pollution data obtained from National Air Quality Information System (SINCA) monitoring stations, meteorological information from the Meteorological Directorate of Chile, and socioeconomic information on income poverty level, multidimensional poverty level, unemployment, schooling, overcrowding and health, we constructed a data panel containing daily information at the community level, from 2016 to 2019. Using three ordinary least squares (OLS) regression models, we studied the relationship between socioeconomic variables and each of the pollutants. Our results show that, in general, there is a positive and significant relationship between the level of multidimensional poverty of a population and the totality of regional pollution levels; as well as a negative and significant relationship between unemployment and the different pollution levels. Finally, there is a negative and significant relationship between the level of citizen's education and pollution. The main objective of this study was to investigate the possible relationships between socio-economic variables and pollution, in order to generate evidence to aid implementation of environmental public policies.

Relationship between pollution levels and poverty: regions of Antofagasta, Valparaiso and Biobio, Chile

“…In the particular case of the variable of interest, the results confirm the assumptions showing how multidimensional poverty is positively and significantly related to all pollutants; these results confirm the relationship found by Herrera et al [13]. In the case of unemployment, a positive and significant relationship is shown for PM10 and PM2.5 and a negative and significant correlation for SO 2 , the latter being closely linked to economic activity, since less pollution is generated when there is less economic activity.…”

“…According to the National Institute of Human Rights [10] during 2018, emissions and contamination of natural resources resulting from energy, mining, agro-industrial and forestry projects, represented 60% of the total number of conflicts [11,12]. The territories involved present worrying figures of multidimensional poverty, insufficient public health services and a lax environmental policy regarding the exploitation of natural resources and emissions of polluting particles [13] to such an extent that some of these localities have become sacrifice zones, which have increased their inequality indicators [9,14].…”