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dc.contributor.authorKolarov, Georgy
dc.contributor.authorGhelev, Chavdar
dc.contributor.authorIliev, Mihail
dc.contributor.authorPaneva, Daniela
dc.contributor.authorGrigorov, Ivan
dc.contributor.authorNedkov, Ivan
dc.contributor.authorStoyanov, Dimitar
dc.contributor.authorGroudeva, V.
dc.contributor.authorIlieva, Ralitsa
dc.contributor.authorCherkezova-Zheleva, Z.
dc.date.accessioned2021-06-02T10:11:59Z
dc.date.available2021-06-02T10:11:59Z
dc.date.issued2019
dc.identifierONIX_20210602_10.5772/intechopen.87031_427
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/49313
dc.description.abstractLight detection and ranging (LIDAR) atmospheric sensing is a major tool for remote monitoring of aerosol pollution and its propagation in the atmosphere. Combining LIDAR sensing with ground-based aerosol monitoring can form the basis of integrated air-quality characterization. When present, biological atmospheric contamination is transported by aerosol particles of different size known as bioaerosol, whose monitoring is now among the basic areas of atmospheric research, especially in densely-populated large urban regions, where many bioaerosol-emitting sources exist. Thus, promptly identifying the bioaerosol sources, including their geographical coordinates, intensities, space-time distributions, etc., becomes a major task of a city monitoring system. This chapter argues in favor of integrating a LIDAR mapping schematic with in situ sampling and characterization of the bioaerosol in the urban area. The measurements, data processing, and decision-making aimed at preventing further atmospheric contamination should be performed in a near-real-time mode, which imposes certain demands on the typical LIDAR schematics, including long-range sensing as a critical parameter, especially over large areas (10 – 100 km2). In this chapter, we describe experiments using a LIDAR schematic allowing near-real-time long-distance measurements of urban bioaerosol combined with its ground-based sampling and physicochemical and biological studies.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technologyen_US
dc.subject.otherLIDAR monitoring, particulate matter, atmospheric pollution, contaminations
dc.titleChapter Long-Distance LIDAR Mapping Schematic for Fast Monitoring of Bioaerosol Pollution over Large City Areas
dc.typechapter
oapen.identifier.doi10.5772/intechopen.87031
oapen.relation.isPublishedBy09f6769d-48ed-467d-b150-4cf2680656a1
oapen.relation.isFundedByH2020-INFRAIA-2014-2015
oapen.grant.number654109
oapen.grant.acronymACTRIS-2


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