Abstract

Abstract. The inhabitants of Santiago, Chile have been exposed to harmful levels of air pollutants for decades. The city's poor air quality is a result of steady economic growth, and stable atmospheric conditions adverse to mixing and ventilation that favor the formation of oxidants and secondary aerosols. Identifying and quantifying the sources that contribute to the ambient levels of pollutants is key for designing adequate mitigation measures. Estimating the evolution of source contributions to ambient pollution levels is also paramount to evaluating the effectiveness of pollution reduction measures that have been implemented in recent decades. Here, we quantify the main sources that have contributed to fine particulate matter (PM2. 5) between April 1998 and August 2012 in downtown Santiago by using two different source-receptor models (PMF 5.0 and UNMIX 6.0) that were applied to elemental measurements of 1243 24 h filter samples of ambient PM2.5. PMF resolved six sources that contributed to ambient PM2. 5, with UNMIX producing similar results: motor vehicles (37.3 ± 1.1 %), industrial sources (18.5 ± 1.3 %), copper smelters (14.4 ± 0.8 %), wood burning (12.3 ± 1.0 %), coastal sources (9.5 ± 0.7 %) and urban dust (3.0 ± 1.2 %). Our results show that over the 15 years analyzed here, four of the resolved sources significantly decreased [95 % confidence interval]: motor vehicles 21.3 % [2.6, 36.5], industrial sources 39.3 % [28.6, 48.4], copper smelters 81.5 % [75.5, 85.9], and coastal sources 58.9 % [38.5, 72.5], while wood burning did not significantly change and urban dust increased by 72 % [48.9, 99.9]. These changes are consistent with emission reduction measures, such as improved vehicle emission standards, cleaner smelting technology, introduction of low-sulfur diesel for vehicles and natural gas for industrial processes, public transport improvements, etc. However, it is also apparent that the mitigation expected from the above regulations has been partially offset by the increasing amount of private vehicle use in the city, with motor vehicles becoming the dominant source of ambient PM2. 5 in recent years. Consequently, Santiago still experiences ambient PM2. 5 levels above the annual and 24 h Chilean and World Health Organization standards, and further regulations are required to reach ambient air quality standards.

Highlights

  • Santiago (33.5◦ S, 70.5◦ W, 500 m above sea level; a.s.l.) is the largest metropolitan area in Chile and the seventh in South America, with a population of around 7 million

  • Central Chile is characterized by significant interannual variability connected to the El Niño Southern Oscillation (ENSO) and longer-term variability associated with the Pacific Decadal Oscillation (Garreaud et al, 2009)

  • Lead is a classical tracer of motor vehicle emissions, it is still possible to identify and quantify the motor vehicles source using other species or ratios between species as we did in this work with Cr, Ni, Cu and Zn

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Summary

Introduction

Santiago (33.5◦ S, 70.5◦ W, 500 m above sea level; a.s.l.) is the largest metropolitan area in Chile and the seventh in South America, with a population of around 7 million. Subsynoptic features known as coastal lows recurrently intensify the subsidence conditions (Rutllant and Garreaud, 1995), and their occurrence is linked to acute pollution episodes in winter (Gallardo et al, 2002; Saide et al, 2011). Over the last 6 to 7 years, central and southern Chile has been affected by an extended and persistent drought, partly caused by natural variability and partly linked to a global warming trend (Boisier et al, 2016; CR2, 2015). All these conditions produce favorable conditions for the accumulation of emissions, and the generation of secondary pollutants. Some studies have presented PBLH estimates retrieved from ceilometer readings (Muñoz and Undurraga, 2010; Muñoz and Alcafuz, 2012); the data show a distinctive seasonality with lower (higher) values for the austral winter (summer) seasons, prompted by the synoptic meteorological conditions discussed above, but the PBLH shows no significant trend between 2008 and 2015

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