Report of Particulate Matter Emissions During the 2015 Fire at Fuel Tanks in Santos, Brazil

Abstract

We report a study of the particulate matter emissions related to the 2015 fire outbreak at a fuel tank storage facility located at Santos, a coastal city in Brazil. The facility, managed by the company Ultracargo, had oil tanks (filled with gasoline and ethanol) destroyed by fire that lasted more than a week, between 2nd and 9th April. In this article, we present the atmospheric concentration analysis of particulate matter (PM10) measured over the entire month of April 2015 by the 2 closest stations that integrate the air quality monitoring system of the São Paulo State Environmental Company (CETESB). The results were compared with similar data from the same period of the yesteryear (April 2014). The results were also complemented by the air masses trajectories over the region (obtained with HYSPLIT/NOAA software). Our results do indicate a subtle increase in the particulate concentration during the days of the fire, followed by a fast dissipation over the subsequent weeks. The observed plume dispersion discussion is made considering the meteorological patterns of the region and other environmental and health reported impacts related to the accident.

The Impact of Industrial Fires in Urban Settings: Monitoring, Modelling, Health, and Environmental Justice Perspectives

“…Metal contamination can also be an issue with some fires, depending on the nature of the material that is burning [15]. Land contamination can additionally give rise to waterway pollution through leachate-runoff, and the waterways can be polluted directly by effluent from firefighting activities [23,24].…”

“…These models can be used in backwards-mode to help in the identification of sources of elevated pollution concentrations [17,42] or odour [49]. They can also be used in forward mode to either calculate ground level concentrations and overall plume behaviour [46] or identify the ambient monitoring stations that a plume is likely to have passed over, thus allowing incident-relevant data on airborne pollutants to be identified [4,24,43].…”