Journals / Atmospheric Pollution Research / 2016 / Cilt: 7 - Sayı: 6

A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station

Pages
990–1003
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The comprehensive evaluationresults, through the comparison with the observed data, showed good performances pointing outthe reliability of the estimated concentration fields around the site and consequently of the assessmentof its representativeness area.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The evaluation of the spatial representativeness of air quality monitoring stations is of fundamentalrelevance when observed concentration levels are used in air quality assessment.
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Key Findings & Data:Acomprehensive characterization of the main anthropogenic emissions of the area was carried out, withdetailed treatment of dust emission by wind erosion from industrial mineral piles; a Lagrangianmodelling approach was chosen to simulate PM10 dispersion patterns, to achieve a reliable and highresolution description of concentration variability around the site.
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Conclusion & Impact:The comprehensive evaluationresults, through the comparison with the observed data, showed good performances pointing outthe reliability of the estimated concentration fields around the site and consequently of the assessmentof its representativeness area.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

The evaluation of the spatial representativeness of air quality monitoring stations is of fundamentalrelevance when observed concentration levels are used in air quality assessment. Since no referencemethod is provided, there is a need to develop tools for its quantitative assessment. In this paper we testa recently developed methodology for spatial representativeness area assessment, based on the analysisof time series of model concentrations by means of a Concentration Similarity Frequency (CSF) function,on the Taranto-via Machiavelli industrial monitoring station, located in a mid-size city in Southern Italy.The complex territorial context, the peculiar anthropogenic emissions features, dominated by thecontribution of the largest steelworks in Europe, and the critical situation of human health in the citymake this application an interesting case study to assess the portability of the CSF approach, so farapplied only to background stations, to industrial sites that experience high concentration variability. Acomprehensive characterization of the main anthropogenic emissions of the area was carried out, withdetailed treatment of dust emission by wind erosion from industrial mineral piles; a Lagrangianmodelling approach was chosen to simulate PM10 dispersion patterns, to achieve a reliable and highresolution description of concentration variability around the site. The resulting representativeness areaof the station is 0.067 km2, fulfilling EU prescriptions for industrial stations. The comprehensive evaluationresults, through the comparison with the observed data, showed good performances pointing outthe reliability of the estimated concentration fields around the site and consequently of the assessmentof its representativeness area.

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Cite This Article

VİTALİ, L., MORABİTO, A., ADANİ, M., ASSENNATO, G., CİANCARELLA, L., CREMONA, G., GİUA, R., PASTORE, T., PİERSANTİ, A., RİGHİNİ, G., RUSSO, F., SPAGNOLO, S., TANZARELLA, A., TİNARELLİ, G., ZANİNİ, G. (2016). A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station. Atmospheric Pollution Research, Cilt: 7 - Sayı: 6, 990–1003. https://ajindex.com/articles/351582

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