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Particulate matter characterization in a steelworks using conventional sampling and innovative lidar observations 被引量:1
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作者 Benjamin Guinot Beatriz Gonzalez +1 位作者 Julia Perim De Faria Sumita Keclia 《Particuology》 SCIE EI CAS CSCD 2016年第5期43-51,共9页
Particulate matter (PM) emissions from steelworks cause public concern. Although end-of-pipe and pro- cess integrated measures have led to a significant drop in emissions of large particles from stacks, fine aerosol... Particulate matter (PM) emissions from steelworks cause public concern. Although end-of-pipe and pro- cess integrated measures have led to a significant drop in emissions of large particles from stacks, fine aerosols were not specifically considered, nor were emissions from fugitive and open sources. In this study, we deployed aerosol samplers together with a scanning ultra-violet (UV) lidar to characterize total suspended particles (TSP), PM10, and PM2.5, in emissions from a large integrated steelworks in Spain over a 16-day period. We determined the content of carbonaceous, soluble inorganic, mineral dust, and metal species. A positive matrix factorization was carried out on our dataset. Despite mineral dust being predominant in all size fractions, the steelworks was clearly a source of carbonaceous species, resulting in production of secondary inorganic aerosols. In particular, stack emissions were a major contributor of fine particles, while open sources dominated the emissions of TSP, yielding up to 80% of particles larger than PM10. UV lidar provided 2D maps of aerosols in real time, with an ability to detect PM emissions and to visualize complex plumes. We suggest that air quality management of steelworks needs to focus on controlling large and coarse oarticle emissions, esoeciallv those from onen sources. 展开更多
关键词 fine aerosols Fugitive emissions Open sources Chemical composition Trace metals UV lidar
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