PM10 samples were collected in a site of Apulia region (South-East Italy) near a steel plant when the winds were blowing from the NW and the SE to exclude and include, respectively, the contribution of the industrial source in order to study the aerosol particles in detail and attribute them to the most appropriate emission sources. Size, morphology and chemical composition of 6500 individual particles, with an equivalent spherical diameter (ESD) between 0.4 - 1 mu m, 1 - 2.5 mu m and 2.5 - 10 mu m, were analysed by scanning electron microscopy coupled with energy dispersive X-ray analysis (SEM EDX). These particles were classified in the thirteen groups: aluminosilicates, silicates, iron oxides, metal oxides, iron mixtures, aluminosilicates with sulphur, calcium sulphates, silicate-sulphate mixed particles, carbonates, carbonates-silicates, soot, biological particles and carbon rich particles. Source apportionment analyses were carried out separately for the three dimensional ranges considered and for the two wind directions from North-West and South-East and nine main sources were distinguished. The soil and the soot components are higher when the wind blow from the NW than the SE, while the anthropogenic sources are evident with the wind from the SE due to the presence of iron and carbonaceous particles characterized by typical spherical shapes and chemical elements as Ca, Na and K which could to be indicative of industrial activity. The single particle analysis let better identify the emission sources that persist on the territory, attributing to them the particles characterized by peculiar morphology and chemical composition.

In this study, data on the hourly concentrations of the total particle-bound Polycyclic Aromatic Hydrocarbons (p-PAHs) collected between 1 August 2013 and 31 August 2014 by the air quality fence monitoring network of the biggest European steel plant, were analyzed. In contrast with what was predicted, the total p-PAH concentration did not decrease with distance from the steel plant, and higher concentrations were registered at the Orsini site, in the urban settlement, relative to the Parchi site, which is nearest to the coke ovens. Therefore, in order to identify and explain the cause of these high concentrations, a tailored monitoring experiment was carried out on a specific monitoring pathway by using a total p-PAHs monitor placed onto a cart. The real-time monitoring of the total p-PAH concentration on the road revealed to be a useful tool, which identified vehicular traffic as an important source of p-PAHs and highlighted the possible high short-term effect that vehicular traffic sources could have on the health of the exposed human population. Moreover, the study focused attention on the importance of the spatial representativeness of fixed monitoring stations, especially in a highly complex industrial area such as Taranto (Southern Italy).

OBJECTIVES: to estimate the environmental and health impact attributable to PM2.5 emissions from the ex-ILVA steel plant in Taranto and the ENEL power plant in Brindisi (Apulia Region, Southern Italy). DESIGN: a SPRAY Lagrangian dispersion model was used to estimate PM2.5 concentrations and population weighted exposures following the requirements of the Integrated Environmental Authorization (IEA) of the two plants under study. Available concentration-response functions (OMS/HRAPIE and updates) were used to estimate the number of attributable premature deaths. SETTING AND PARTICIPANTS: residents in the 40 municipalities of the domains of the VDS (assessment of health damage, according to the Regional Law n. 21/2012) of Brindisi (source: Italian National Institute of Statistics 2011 Census) and residents in Taranto, Statte, and Massafra (source: cohort study). MAIN OUTCOME MEASURES: mortality from natural causes, cardiovascular and respiratory diseases, and lung cancer attributable to PM2.5. Incremental lifetime cumulative risks (ILCRs) for lung cancer associated to PM2.5 exposure. RESULTS: there was a reduction of the estimated impacts from the pre to the post IEA-scenarios in both Taranto and Brindisi. In Taranto, ILCRs greater than 1x10(-4) were estimated in 2010 and 2012; the ILCR was greater than 1x10(-4) in the district of Tamburi (near the plant) also for the 2015 scenario. ILCRs estimated for Brindisi were between 1x10(-6) and 4x10(-5). CONCLUSIONS: the Integrated Environmental Health Impact Assessment confirmed the results of the VDS conducted according to the toxicological risk assessment approach. An unacceptable risk was estimated for Tamburi also for the 2015 scenario, characterized by a production of 4.7 million tons of steel, about half compared to one foreseen by the IEA (8 mt.).

Background: A large steel plant close to the urban area of Taranto (Italy) has been operating since the sixties. Several studies conducted in the past reported an excess of mortality and morbidity from various diseases at the town level, possibly due to air pollution from the plant. However, the relationship between air pollutants emitted from the industry and adverse health outcomes has been controversial. We applied a variant of the "differencein-differences" (DID) approach to examine the relationship between temporal changes in exposure to industrial PM10 from the plant and changes in cause-specific mortality rates at area unit level. Methods: We examined a dynamic cohort of all subjects (321,356 individuals) resident in the Taranto area in 1998-2010 and followed them up for mortality till 2014. In this work, we included only deaths occurring on 2008-2014. We observed a total of 15,303 natural deaths in the cohort and age-specific annual death rates were computed for each area unit (11 areas in total). PM10 and NO2 concentrations measured at air quality monitoring stations and the results of a dispersion model were used to estimate annual average population weighted exposures to PM10 of industrial origin for each year, area unit and age class. Changes in exposures and in mortality were analyzed using Poisson regression. Results: We estimated an increased risk in natural mortality (1.86%, 95% confidence interval [CI]: -0.06, 3.83%) per 1 mu g/m(3) annual change of industrial PM10, mainly driven by respiratory causes (8.74%, 95% CI: 1.50, 16.51%). The associations were statistically significant only in the elderly (65+ years). Conclusions: The DID approach is intuitively simple and reduces confounding by design. Under the multiple assumptions of this approach, the study indicates an effect of industrial PM10 on natural mortality, especially in the elderly population.

Odor monitoring has been an issue of concern for a long time and new devices and innovative approaches to recognize and quantify odors, to characterize emission sources and to activate mitigation systems were developed. Chemical characterization of odorants provides useful information about composition and mechanisms of formation but fails in the reconstruction of the final odor perception. Electronic noses remain unmatched devices when the cheapest approach for high temporal resolution monitoring of odorous phenomena is required but their use implies a robust training and is affected by poor reliability. Synergistic approach based on chemical characterization, dynamic olfactometry and electronic noses reveals to be the best way to a) characterize odors; b) evaluate their concentration; c) develop innovative and tailored monitoring systems. Therefore, this review aims to examine the recently advanced in odor detection and monitoring methods highlighting limits and potentialities and proposing the integration of them as a strategic approach.

A modelling system based on FARM chemical transport model is applied to assess the air quality (AQ) over the Apulia region (Southern Italy) for 2013. The most relevant pollutant sources in the region are a steel plant, the largest in Europe (in the Taranto area), a coal fired power plant, the second most powerful in Italy (in the Brindisi area) and biomass burning for residential heating. Simulation results indicate exceedances for PM10 daily limit value and benzo(a) pyrene (B(a) P) annual limit values occurring in some areas. The evaluation of the model performance has been conducted by using the software DELTA Tool, developed within FAIRMODE to support the application of the EU Air Quality Directive. Results show good performance of the model, with a tendency to underestimate PM10 and O-3 levels. These results suggest the use of this modelling strategy for further source apportionment studies, in order to identify the sources that mainly affect air quality and to implement proper emission control strategies.

Figure 3: Comparison of the time series of PM10 concentrations measured by the control unit at Don Minzoni (top) and Fanin (bottom) and the time series of the modeled concentrations (includedbackground) extracted at the correspondingpoints grid, from 1 to 13 December 2016 Table 1: PM10 forecast evaluation and skill scores analysis for MicroSPRAY model over the entire period considered for simulation (1-13 December 2016)

BACKGROUND:Exposure to heavy metals has been associated with kidney disease. We investigated the spatial distribution of kidney disease in the industrially contaminated site of Taranto.METHODS:Cases were subjects with a first hospital discharge diagnosis of kidney disease. Cases affected by specific comorbidities were excluded. Standardized Hospitalization Ratios (SHRs) were computed for low/high exposure area and for modeled spatial distribution of cadmium and fine particulate matter.RESULT:Using the high/low exposure approach, in subjects aged 20-59 years residing in the high exposure area a significant excess of hospitalization was observed in males and a non-significant excess in females. No excesses were observed in subjects aged 60 years and over. The analysis by the modeling approach did not show a significant association with the greatest pollution impact area.CONCLUSION:Due to the excesses of hospitalization observed in the high/low exposure approach, a continuing epidemiological surveillance of residents and occupational groups is warranted.

Children spend a large amount of time in school environments and when Indoor Air Quality (IAQ) is poor, comfort, productivity and learning performances may be affected. The aim of the present study is to characterize IAQ in a primary school located in Taranto city (south of Italy). Because of the proximity of a large industrial complex to the urban settlement, this district is one of the areas identified as being at high environmental risk in Italy. The study carried out simultaneous monitoring of indoor and outdoor Volatile Organic Compounds (VOC) concentrations and assessed different pollutants’ contributions on the IAQ of the investigated site. A screening study of VOC and determination of Benzene, Toluene, Ethylbenzene, Xylenes (BTEX), sampled with Radiello® diffusive samplers suitable for thermal desorption, were carried out in three classrooms, in the corridor and in the yard of the school building. Simultaneously, Total VOC (TVOC) concentration was measured by means of real-time monitoring, in order to study the activation of sources during the monitored days. The analysis results showed a prevalent indoor contribution for all VOC except for BTEX which presented similar concentrations in indoor and outdoor air. Among the determined VOC, Terpenes and 2-butohxyethanol were shown to be an indoor source, the latter being the indoor pollutant with the highest concentration.

This study provided a useful approach for assessing the impact of industrial sources on surrounding, especially in a sensitive industrial area as Taranto (South of Italy). Taranto is one of the most industrialized Italian towns, where several emission sources operate simultaneously in proximity to the urban settlement. An intensive monitoring campaign of PAHs was carried out from January 28th to July 30th, 2011, in seven sites located in residential settlement around the industrial area and in the city center. The collected data were integrated with the information about wind direction and speed by means bivariate polarplot in order to characterize and localize the industrial sources. High BaP concentrations were detected especially when Benzene to Toluene ratio (B/T ratio) values excedeed 1 and all receptor sites were downwind to the steel plant. Moreover, in order to discriminate among PAH sources and quantify their contributions, a source apportionment analysis of the collected data was provided by means Principal component Analysis (PCA) and Positive Matrix Factorization (PMF) methods. Finally, the processing of PMF5.0 output by bivariate polar plot, confirmed the impact of steel plant on both industrial sites downwind the steel plant and the city center. B[a]P apportionment was quite similar for industrial and urban sites: the traffic source contributed only 11% and 24% to B[a]P measured at two sites, respectively. Therefore, the proximity of Taranto downtown to industrial pole makes negligible all other source contributions to PAH concentrations.

BACKGROUND:Particulate matter (PM) is the most efficient vehicle for the inhalation and absorption of toxic substances into the body.METHOD:The present study was aimed at testing the hypothesis that PM10 samples collected on quartz filters exert an angiogenic activity in vivo in the chick embryo chorioallantoic membrane (CAM) assay.RESULTS:When the low, medium, and high PM10 concentrations filters were tested in the CAM assay, an increasing number of microvessels was detectable after 4 days of applications of the filters. Moreover, at histological level, numerous microvessels and a dense inflammatory infiltrate were recognizable in the CAM mesenchyme.CONCLUSION:Our data show a clear dose-response relationship between the dose variable (PM10 and Bap) and the outcome variable. So far, the PM10 target value is determined on the basis of regulatory agreements and is not health-based. In addition, the mere gravimetric measure of PM10 cannot be considered a fully reliable surrogate of the overall toxicity of the mixture.

This study aims to investigate the air quality in primary school placed in district of Taranto (south of Italy), an area of high environmental risk because of closeness between large industrial complex and urban settlement. The chemical characterization of PM2.5 was performed to identify origin of pollutants detected inside school and the comparison between indoor and outdoor levels of PAHs and metals allowed evaluating intrusion of outdoor pollutants or the existence of specific indoor sources. The results showed that the indoor and outdoor levels of PM2.5, BaP, Cd, Ni, As, and Pb never exceeded the target values issued by World Health Organization (WHO). Nevertheless, high metals and PAHs concentrations were detected especially when school were downwind to the steel plant. TheI/Oratio showed the impact of outdoor pollutants, especially of industrial markers as Fe, Mn, Zn, and Pb, on indoor air quality. This result was confirmed by values of diagnostic ratio as B(a)P/B(g)P, IP/(IP + BgP), BaP/Chry, and BaP/(BaP + Chry), which showed range characteristics of coke and coal combustion. However, Ni and As showedI/Oratio of 2.5 and 1.4, respectively, suggesting the presence of indoor sources.

The evaluation of the spatial representativeness of air quality monitoring stations is of fundamental relevance when observed concentration levels are used in air quality assessment. Since no reference method is provided, there is a need to develop tools for its quantitative assessment. In this paper we test a recently developed methodology for spatial representativeness area assessment, based on the analysis of 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 the contribution of the largest steelworks in Europe, and the critical situation of human health in the city make this application an interesting case study to assess the portability of the CSF approach, so far applied only to background stations, to industrial sites that experience high concentration variability. A comprehensive characterization of the main anthropogenic emissions of the area was carried out, with detailed treatment of dust emission by wind erosion from industrial mineral piles; a Lagrangian modelling approach was chosen to simulate PM10 dispersion patterns, to achieve a reliable and high resolution description of concentration variability around the site. The resulting representativeness area of the station is 0.067 km(2), fulfilling EU prescriptions for industrial stations. The comprehensive evaluation results, through the comparison with the observed data, showed good performances pointing out the reliability of the estimated concentration fields around the site and consequently of the assessment of its representativeness area. Copyright (C) 2016 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.

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.

Introduction. Although the long-term effect of air pollution on mortality has been well studied, the health effects of industrial emissions are less clear and the relevant time-windows of exposure must be established. We conducted a cohort study to examine the association between residential exposure to air pollution from a large steel plant (ILVA), located in Taranto (South Italy) and cause-specific mortality. Methods. The cohort included all (321,356 subjects) residents in the area in 1998, followed until 2013. Exposure to PM10 and SO2 originating from the steel plant at each residential address in 2010 was assigned using a Lagrangian dispersion model. A backward (and forward) extrapolation back to 1965 was done on the basis of industry steel production, emission data, and the spatial pattern of pollutants. The time-dependent annual average exposure and the cumulative exposure of the last 35 years were used in Cox proportional-hazard models to investigate the effect of industrial air pollutants on mortality. The latency of effects was explored with distributed-lag models. Results. A total of 33,042 subjects died from natural causes by the end of the follow-up period. Both industrial PM10 and SO2 at lag 0 were associated with natural mortality: HR 1.04 (95% Confidence Interval (CI):1.02-1.06) and 1.09 (95%CI:1.05-1.12) for each 10µg/m3, respectively. Stronger associations were observed for heart diseases (HR 1.05 for PM10 and 1.11 for SO2) and acute myocardial infarction (HR 1.10 for PM10 and 1.29 for SO2). Similar effects were found with the 35-year cumulative exposure. The distributed-lag models for natural mortality showed that the effects were due to both the recent exposure (previous 5 years) and the exposures in the distant past (30-35 years lag). Conclusions. Concurrent and cumulative exposures to industrial PM10 and SO2 were associated with mortality in the cohort. Both recent and distant exposures are responsible for the negative effects on mortality.

II International Conference on Atmospheric Dust DUST 2016 Castellaneta Marina (Taranto), Italy June, 12-17, 2016. Abstract Poster

Introduction Aim of this study was the impact assessment of emissions produced by power plants, located in the Brindisi area in southern Italy, over the period from 1991 to 2014. This assessment provided a likely temporal and spatial reconstruction of annual mean population exposure to primary pollutants emitted by the plants. Methods The annual average concentrations of PM10 and SO2 were estimated through a modeling system including the SWIFT diagnostic meteorological model, the SURFPRO turbulence preprocessor and the SPRAY Lagrangian dispersion model. Most of the activity focused on the reconstruction of the emissions produced by the power plants stacks and by the storage and handling of coal stockyards. Different information sources, database and archives were considered and a large amount of data (production data, fuel consumption, storage material, etc.) were taken into account. A comparison of measured and modelled concentrations was also performed for SO2. Results Ground concentrations of SO2 and PM10 were modelled for each year. For SO2 the modelled annual mean concentration, extracted at monitoring station located in the maximum impact area, was characterized from 1991 to 1997 by high values (33-41 µg/m3) decreasing rapidly by 65% in the 1998-2002 period and 90% in the next years. To evaluate the model performance a standard statistics have been considered. SO2 comparison results showed a good accordance for all indexes that improves from 1998 (i.e., FAC2 56÷100%) when all stack emissions came from measures obtained through Automatic Measuring System. Conclusions This study is the first retrospective reconstruction of power plants emissions and of their impacts in the studied area. Moreover, the application of an advanced tridimensional dispersion model, never used in previous studies, produced satisfactory results if compared with observations. Finally, the results of this study were used as exposure data input for an epidemiologic cohort study in this area.