Brescia is a city located in Northern Italy which suffers the impact of its large scale industrial development on the surrounding environment. This development started at the beginning of 1900 when different industries such as foundry, steel, mechanical, weapon and chemical grew up. Among chemical industries, Caffaro S.p.a. produced PCBs for about 50 years (1930-1984) and its surrounding areas were found to be heavily contaminated with high concentrations in soil at mg/kg levels. For this reason this area was declared National Relevance Site (SIN) for remediation by the Italian authorities. The aim of the present study was to investigate the potential of the contaminated area in driving the PCB contamination at regional scale up to about 100 km from the point source and the current effects on air concentrations. Different sampling campaigns were organized to collect samples of soil and leaves along four 100 km transects (one sampling point every 7 km) that ran in NW, NE, SW and SE directions considering the production plant as starting point. Woods soils were chosen to avoid to collect samples altered by tillage activities. Leaves were sampled above the corresponding soil sample. In each sample the following PCB congeners were determined: PCB 28, PCB 52, PCB 101, PCB 153, PCB 138, PCB 180 and PCB 209. PCB 209 was included because it can be considered a marker of Caffaro contamination, the only world producer of Fenclor DK, a technical grade decachlorobiphenyl mixture. The results were analyzed to understand the presence of a spatial gradient of decreasing pollutant concentration with distance from the source. Fingerprint data were used to run a number of simulations with a dynamic air-vegetation-litter-soil model in order to 1) predict the order of magnitude of fluxes at each point considering the actual soil and leaf concentrations, 2) understand the source strength in order to predict a temporal emission profile from the site, 3) evaluate the importance of other sources and processes involved in the contamination at a regional scale.
Regional scale modelling of PCBs from a highly contaminated site in Northern Italy
TERZAGHI, ELISA;MORSELLI, MELISSA;RASPA, GIUSEPPE;DI GUARDO, ANTONIO
2017-01-01
Abstract
Brescia is a city located in Northern Italy which suffers the impact of its large scale industrial development on the surrounding environment. This development started at the beginning of 1900 when different industries such as foundry, steel, mechanical, weapon and chemical grew up. Among chemical industries, Caffaro S.p.a. produced PCBs for about 50 years (1930-1984) and its surrounding areas were found to be heavily contaminated with high concentrations in soil at mg/kg levels. For this reason this area was declared National Relevance Site (SIN) for remediation by the Italian authorities. The aim of the present study was to investigate the potential of the contaminated area in driving the PCB contamination at regional scale up to about 100 km from the point source and the current effects on air concentrations. Different sampling campaigns were organized to collect samples of soil and leaves along four 100 km transects (one sampling point every 7 km) that ran in NW, NE, SW and SE directions considering the production plant as starting point. Woods soils were chosen to avoid to collect samples altered by tillage activities. Leaves were sampled above the corresponding soil sample. In each sample the following PCB congeners were determined: PCB 28, PCB 52, PCB 101, PCB 153, PCB 138, PCB 180 and PCB 209. PCB 209 was included because it can be considered a marker of Caffaro contamination, the only world producer of Fenclor DK, a technical grade decachlorobiphenyl mixture. The results were analyzed to understand the presence of a spatial gradient of decreasing pollutant concentration with distance from the source. Fingerprint data were used to run a number of simulations with a dynamic air-vegetation-litter-soil model in order to 1) predict the order of magnitude of fluxes at each point considering the actual soil and leaf concentrations, 2) understand the source strength in order to predict a temporal emission profile from the site, 3) evaluate the importance of other sources and processes involved in the contamination at a regional scale.
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