Abstract. Vertical aerosol profiles were directly measured over the city of Milan during three years (2005)(2006)(2007)(2008) of field campaigns. An optical particle counter, a portable meteorological station and a miniaturized cascade impactor were deployed on a tethered balloon. More than 300 vertical profiles were measured, both in winter and summer, mainly in conditions of clear, dry skies.The mixing height was determined from the observed vertical aerosol concentration gradient, and from potential temperature and relative humidity profiles. Results show that inter-consistent mixing heights can be retrieved highlighting good correlations between particle dispersion in the atmosphere and meteorological parameters. Mixing height growth speed was calculated for both winter and summer showing the low potential atmospheric dispersion in winter.Aerosol number size distribution and chemical composition profiles allowed us to investigate particle behaviour along height. Aerosol measurements showed changes in size distribution according to mixing height. Coarse particle profiles (d p >1.6 µm) were distributed differently than the fine ones (d p <1.6 µm) were, at different heights of the mixing layer. The sedimentation process influenced the coarse particle profiles, and led to a reduction in mean particle diameter for those particles observed by comparing data above the mixing height with ground data (−14.9±0.6% in winter and −10.7±1.0% in summer). Conversely, the mean particle diameter of fine particles increased above the mixing height under stable atmospheric conditions; the average inCorrespondence to: L. Ferrero (luca.ferrero@unimib.it) crease, observed by comparing data above the mixing height with ground data, was +2.1±0.1% in winter and +3.9±0.3% in summer. A hierarchical statistical model was created to describe the changes in the size distribution of fine particles along height. The proposed model can be used to estimate the typical vertical profile characterising launches within prespecified groups starting from: aerosol size and meteorological conditions measured at ground-level, and a mixing height estimation. The average increase of fine particle diameter, estimated on the basis of the model, was +1.9±0.5% in winter and +6.1±1.2% in summer, in keeping with experimental findings.

Currently people are aware of the risk related to pollution exposure. Thus odor annoyances are considered a warning about the possible presence of toxic volatile compounds. Malodor often generates immediate alarm among citizens, and electronic noses are convenient instruments to detect mixture of odorant compounds with high monitoring frequency. In this paper we present a study on pattern recognition on ambient air composition in proximity of a gas and oil pretreatment plant by elaboration of data from an electronic nose implementing 10 metal-oxide-semiconductor (MOS) sensors and positioned outdoor continuously during three months. A total of 80,017 e-nose vectors have been elaborated applying the self-organizing map (SOM) algorithm and then k-means clustering on SOM outputs on the whole data set evidencing an anomalous data cluster. Retaining data characterized by dynamic responses of the multisensory system, a SOM with 264 recurrent sensor responses to air mixture sampled at the site and four main air type profiles (clusters) have been identified. One of this sensor profiles has been related to the odor fugitive emissions of the plant, by using ancillary data from a total volatile organic compound (VOC) detector and wind speed and direction data. The overall and daily cluster frequencies have been evaluated, allowing us to identify the daily duration of presence at the monitoring site of air related to industrial emissions. The refined model allowed us to confirm the anomaly detection of the sensor responses.

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This study aims to monitor Volatile Organic Compounds (VOCs) and odour annoyance perceived by the exposed population living nearby a petroleum plant through an integrated high temporal resolution methodological approach. The area under investigation is considered one of the most critical industrial areas of the South of Italy (Basilicata) because of presence of the largest Italian petroleum plant, called the "Center Olio Val d'Agri" (COVA). In fact, VOCs and odours emitted from extraction processes, storage tanks and/or gas pipelines may have an adverse impact on health and life quality of population living near the plant. Therefore, in order to assess the potential impact on nearby urban settlements, two monitoring campaigns were carried out. The first campaign was conducted during 2011 and allowed to integrate the information about odours, monitored by means of electronic nose (e-nose), with meteorological data (wind speed and direction) and population complaints reported on questionnaires. In the second one (from 1st January to 30th July 2017), the previous approach has been improved with an integrated system consisting of photoionization detector (PID) for VOCs monitoring, a video camera and a telephonic system able to systematize in real time the population complaints. Experimental data obtained revealed that there was correspondence between the VOCs concentration peaks, odour events and population complaints. Moreover, this study highlighted that technologies for high temporal resolution monitoring of both VOCs and odours integrated in a unique system are able to provide real time information about the emissive sources and odor annoyance and to promptly evaluate the impact on the exposed population.

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