ArticleInternational journal of environmental research and public health2016
Automated Collection of Real-Time Alerts of Citizens as a Useful Tool to Continuously Monitor Malodorous Emissions.
Article in International journal of environmental research and public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Application of Machine Learning for Fenceline Monitoring of Odor Classes and Concentrations at a Wastewater Treatment Plant.Sensors (Basel, Switzerland) · 2021Article
- Assessment of HEnvironmental monitoring and assessment · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The evaluation of odor emissions and dispersion is a very arduous topic to face; the real-time monitoring of odor emissions, the identification of chemical components and, with proper certainty, the source of annoyance represent a challenge for stakeholders such as local authorities. The complaints of people, often not systematic and variously distributed, in general do not allow us to quantify the perceived annoyance. Experimental research has been performed to detect and evaluate olfactory annoyance, based on field testing of an innovative monitoring methodology grounded in automatic recording of citizen alerts. It has been applied in Taranto, in the south of Italy where a relevant industrial area is located, by using Odortel(®) for automated collection of citizen alerts. To evaluate its reliability, the collection system has been integrated with automated samplers, able to sample odorous air in real time, according to the citizen alerts of annoyance and, moreover, with meteorological data (especially the wind direction) and trends in odor marker compounds, recorded by air quality monitoring stations. The results have allowed us, for the first time, to manage annoyance complaints, test their reliability, and obtain information about the distribution and entity of the odor phenomena, such that we were able to identify, with supporting evidence, the source as an oil refinery plant.
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Registered trials
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