Unraveling the microbiome-metabolome nexus: a comprehensive study protocol for personalized management of Behçet's disease using explainable artificial intelligence.

The presented study protocol outlines a comprehensive investigation into the interplay among the human microbiota, volatilome, and disease biomarkers, with a specific focus on Behçet's disease (BD) using methods based on explainable artificial intelligence. The protocol is structured in three phases. During the initial three-month clinical study, participants will be divided into control and experimental groups. The experimental groups will receive a soluble fiber-based dietary supplement alongside standard therapy. Data collection will encompass oral and fecal microbiota, breath samples, clinical characteristics, laboratory parameters, and dietary habits. The subsequent biological data analysis will involve gas chromatography, mass spectrometry, and metagenetic analysis to examine the volatilome and microbiota composition of salivary and fecal samples. Additionally, chemical characterization of breath samples will be performed. The third phase introduces Explainable Artificial Intelligence (XAI) for the analysis of the collected data. This novel approach aims to evaluate eubiosis and dysbiosis conditions, identify markers associated with BD, dietary habits, and the supplement. Primary objectives include establishing correlations between microbiota, volatilome, phenotypic BD characteristics, and identifying patient groups with shared features. The study aims to identify taxonomic units and metabolic markers predicting clinical outcomes, assess the supplement's impact, and investigate the relationship between dietary habits and patient outcomes. This protocol contributes to understanding the microbiome's role in health and disease and pioneers an XAI-driven approach for personalized BD management. With 70 recruited BD patients, XAI algorithms will analyze multi-modal clinical data, potentially revolutionizing BD management and paving the way for improved patient outcomes.

Identification of a characteristic VOCs pattern in the exhaled breath of post-COVID subjects: are metabolic alterations induced by the infection still detectable?

SARS-CoV-2 is expected to cause metabolic alterations due to viral replication and the host immune response resulting in increase of cytokine secretion and cytolytic activity. The present prospective observational study is addressed at exploring the potentialities of breath analysis in discrimination between patients with a documented previous history of symptomatic SARS-CoV-2 infection and, at the moment of the enrollment, exhibiting a negative nasopharyngeal swab and acquired immunity (post-COVID) and healthy subjects with no evidence of previous SARS-CoV-2 infection (no-COVID). The main purpose is to understand if traces of metabolic alterations induced during the acute phase of the infection are still detectable after negativization, in the form of a characteristic volatile organic compound (VOC) pattern. An overall number of 60 volunteers aged between 25 and 70 years were enrolled in the study (post-COVID: n.30; no-COVID: n. 30), according to well-determined criteria. Breath and ambient air samples were collected by means of an automated sampling system (Mistral) and analyzed by thermal desorption-gas chromatography-mass spectrometry (TD-GC/MS). Statistical tests (Wilcoxon/Kruskal-Wallis test) and multivariate data analysis (principal component analysis (PCA), linear discriminant analysis) were performed on data sets. Among all compounds detected (76 VOCs in 90% of breath samples), 5 VOCs (1-propanol, isopropanol, 2-(2-butoxyethoxy)ethanol, propanal and 4-(1,1-dimethylpropyl)phenol) showed abundances in breath samples collected from post-COVID subjects significantly different with respect to those collected from no-COVID group (Wilcoxon/Kruskal-Wallis test,p-values <0.05). Although not completely satisfactory separation between the groups was obtained, variables showing significant differences between the two groups and higher loadings for PCA are recognized biomarkers of COVID-19, according to previous studies in literature. Therefore, based on the outcomes obtained, traces of metabolic alterations induced by SARS-CoV-2 infection are still detectable after negativization. This evidence raises questions about the eligibility of post-COVID subjects in observational studies addressed at the detection of COVID-19. (Ethical Committee Registration number: 120/AG/11).

Chemical characterisation of PM10 from ship emissions: a study on samples from hydrofoil exhaust stacks.

A chemical characterization of PM10 collected at hydrofoil exhaust stacks was performed conducting two on-board measuring campaigns, with the aim of assessing the ship emission impact on PM10 collected in the coastal area of Naples (Southern Italy) and providing information about the characteristics of this important PM emission source.Samples were analysed determining the contribution of different chemical parameters to PM10's mass, which consisted of polycyclic aromatic hydrocarbons (PAHs) (0.10 ± 0.12%), total carbon (61.9% ± 20.0%, with 40.4% of organic carbon, OC, and 21.5% of elemental carbon, EC) and elemental fraction (0.44% ± 1.00%). Differences in terms of composition and chemical parameter profiles were observed between samples collected during offshore navigation (Off) and samples collected during shunting operations (SO), the latter of higher concern on a local scale. For SO samples, lower contributions of OC and EC were observed (39.7% and 19.6% respectively) compared to Off samples (41.5% and 24.2%), and an increase in terms of elements (from 0.32 to 0.51%) and PAHs (from 0.06 to 0.12%) concentrations was observed. In addition, enrichment factors (EFs) for some elements such as V, Zn, Cd, Cu, Ag and Hg as well as PAHs profile varied significantly between SO and Off. Data presented here were compared with data on chemical composition of PM10 sampled in a tunnel, in a background site and in an urban site in the city of Naples. Results indicated that shipping activities contributed significantly to the emission of V and, in some extent, Zn and Cd; in addition, PAH profiles indicated a greater contribution to urban PM10 from vehicular traffic than shipping emissions. These results can significantly contribute to the correct evaluation of the influence of shipping emission on PM10 generation in urban coastal areas and can be a useful reference for similar studies. The coastal area of Naples is an important example of the coexistence of residential, touristic and natural areas with pollutants emission sources including, among the others, shipping emissions. In this and similar contexts, it is important to distinguish the contribution of each emission source to clearly define environmental control policies.

CO2 concentration monitoring inside educational buildings as a strategic tool to reduce the risk of Sars-CoV-2 airborne transmission.

In order to avoid SARS-CoV-2 transmission inside educational buildings and promote the safe reopening of schools, the Italian Government, in line with the other European countries and in accordance with the WHO recommendations, adopted a contingency plan including actions able to guarantee adequate air ventilation in classrooms. Therefore, in this pilot study, a surveillance activity based on the real-time monitoring of CO2 levels as a proxy of SARS-CoV-2 transmission risk, was conducted inside 9 schools (11 classrooms) located in Apulia Region (South of Italy) during the reopening of schools after the lockdown due to COVID-19 pandemic. More specifically, monitoring activities and data treatment were conducted to evaluate the initial scenario inside the classrooms (first stage of evaluation) and the potential improvements obtained by applying a detailed operating protocol of air ventilation based on specific actions and the simultaneous real time visualization of CO2 levels by non-dispersive infrared (NDIR) sensors (second stage of evaluation). Although, during the first evaluation stage, air ventilation through the opening of windows and doors was guaranteed, 6 (54%) classrooms showed mean values of CO2 higher than 1000 ppm and all classrooms exceeded the recommended CO2 concentration limit value of 700 ppm. The development and implementation of tailored ventilation protocol including the real time visualization of CO2 levels allowed to depict better scenariosAn overall improvement of CO2 levels was indeed registered for all classrooms where teachers were compliant and helpful in the management of the air ventilation strategy. Therefore, this study reports the first evidence-based measures demonstrating that, with the exception of few environments affected by structural limits, the real-time visualization and monitoring of CO2 concentrations allowes effective air exchanges to be implemented and contributes to prevent SARS-CoV-2 transmission. Moreover, on the basis of the monitoring outcomes and in order to ensure adequate air ventilation in educational buildings, a 4 level-risk classification including specific corrective actions for each level was provided.

A sensing network involving citizens for high spatio-temporal resolution monitoring of fugitive emissions from a petroleum pre-treatment plant.

In this study an innovative sensing network consisting of eight photoionization detectors, meteorological sensors, a video camera and a telephonic system able to systematize the population complaints was developed for the monitoring of odor emissions. The development of monitoring approaches with high temporal and spatial resolution and actively involving citizens, is strategic in areas where relevant and also short-term emissive events frequently occur and the conventional approaches fail due to the high variability of fugitive emissions. Moreover, even if unpleasant odors are not necessarily direct triggers of health effects, they could be associated with the release of other harmful compounds. Monitoring approaches also involving citizens are thus strategic tools because odors annoyance perceived by population may be a potential health risk warning. Therefore, the developed sensing network was set up in Val d'Agri (Basilicata, Italy) where a petroleum pre-treatment plant (COVA) rises in a rural and inhabited area. The data collected during the monitoring campaign from the 16th February to the 30th July 2017, showed Total Volatile Organic Compounds (TVOCs) concentrations decreasing moving away from the plant and up to five times higher than levels registered in the closest municipality (Viggiano). Moreover, recurrent short-term critical events characterized by concentration values far above the average of the period and with maximum values ranging from 0.92 to 1.89 ppm, were registered in correspondence with high levels of benzene (up to 23.9 µg/m3) and anemometric conditions able to transport pollutants from COVA to each receptor site. The spatial and temporal distribution of TVOC concentrations proved to be affected by the distance from COVA, wind direction and industrial activities verified using video reportage and citizen claims. Therefore, the developed approach has proven to be a useful tool to credit people's perception of odors and also to quantify citizen exposure to VOCs during short-term events.

Molecular detection of SARS-CoV-2 from indoor air samples in environmental monitoring needs adequate temporal coverage and infectivity assessment.

The relevance of airborne exposure to SARS-CoV-2 in indoor environments is a matter of research and debate, with special importance for healthcare low-risk settings. Experimental approaches to the bioaerosol sampling are neither standardized nor optimized yet, leading in some cases to limited representativity of the temporal and spatial variability of viral presence in aerosols. Airborne viral viability moreover needs to be assessed. A study has been conducted collecting five 24-h PM10 samples in a COVID-19 geriatric ward in late June 2020, and detecting E and RdRp genes by RT-qPCR with a Ct between 36 and 39. The viral RNA detection at Ct = 36 was related to the maximal numerosity of infected patients hosted in the ward. Lacking a direct infectivity assessment for the collected samples an experimental model has been defined, by seeding twelve nasopharyngeal swab extracts from COVID-19 positive patients on Vero E6 cells; only the four extracts with a viral load above E+10 viral copies (approximately Ct<24) have been able to establish a persistent infection in vitro. Therefore, the cytopathic effect, a key feature of residual infectivity, could be considered unlikely for the environmental PM10 samples showing amplification of viral RNA at Ct = 36 or higher. A standardization of airborne SARS-CoV-2 long-term monitoring and of environmental infectivity assessment is urgently needed.

Breath Analysis: Comparison among Methodological Approaches for Breath Sampling.

Despite promising results obtained in the early diagnosis of several pathologies, breath analysis still remains an unused technique in clinical practice due to the lack of breath sampling standardized procedures able to guarantee a good repeatability and comparability of results. The most diffuse on an international scale breath sampling method uses polymeric bags, but, recently, devices named Mistral and ReCIVA, able to directly concentrate volatile organic compounds (VOCs) onto sorbent tubes, have been developed and launched on the market. In order to explore performances of these new automatic devices with respect to sampling in the polymeric bag and to study the differences in VOCs profile when whole or alveolar breath is collected and when pulmonary wash out with clean air is done, a tailored experimental design was developed. Three different breath sampling approaches were compared: (a) whole breath sampling by means of Tedlar bags, (b) the end-tidal breath collection using the Mistral sampler, and (c) the simultaneous collection of the whole and alveolar breath by using the ReCIVA. The obtained results showed that alveolar fraction of breath was relatively less affected by ambient air (AA) contaminants (p-values equal to 0.04 for Mistral and 0.002 for ReCIVA Low) with respect to whole breath (p-values equal to 0.97 for ReCIVA Whole). Compared to Tedlar bags, coherent results were obtained by using Mistral while lower VOCs levels were detected for samples (both breath and AA) collected by ReCIVA, likely due to uncorrected and fluctuating flow rates applied by this device. Finally, the analysis of all data also including data obtained by explorative analysis of the unique lung cancer (LC) breath sample showed that a clean air supply might determine a further confounding factor in breath analysis considering that lung wash-out is species-dependent.

Potential role of particulate matter in the spreading of COVID-19 in Northern Italy: first observational study based on initial epidemic diffusion.

OBJECTIVES: A number of studies have shown that the airborne transmission route could spread some viruses over a distance of 2 meters from an infected person. An epidemic model based only on respiratory droplets and close contact could not fully explain the regional differences in the spread of COVID-19 in Italy. On March 16th 2020, we presented a position paper proposing a research hypothesis concerning the association between higher mortality rates due to COVID-19 observed in Northern Italy and average concentrations of PM10 exceeding a daily limit of 50 µg/m3. METHODS: To monitor the spreading of COVID-19 in Italy from February 24th to March 13th (the date of the Italian lockdown), official daily data for PM10 levels were collected from all Italian provinces between February 9th and February 29th, taking into account the maximum lag period (14 days) between the infection and diagnosis. In addition to the number of exceedances of the daily limit value of PM10, we also considered population data and daily travelling information for each province. RESULTS: Exceedance of the daily limit value of PM10 appears to be a significant predictor of infection in univariate analyses (p<0.001). Less polluted provinces had a median of 0.03 infections over 1000 residents, while the most polluted provinces showed a median of 0.26 cases. Thirty-nine out of 41 Northern Italian provinces resulted in the category with the highest PM10 levels, while 62 out of 66 Southern provinces presented low PM10 concentrations (p<0.001). In Milan, the average growth rate before the lockdown was significantly higher than in Rome (0.34 vs 0.27 per day, with a doubling time of 2.0 days vs 2.6, respectively), thus suggesting a basic reproductive number R0>6.0, comparable with the highest values estimated for China. CONCLUSION: A significant association has been found between the geographical distribution of daily PM10 exceedances and the initial spreading of COVID-19 in the 110 Italian provinces.

Particle-Bound PAHs and Elements in a Highly Industrialized City in Southern Italy: PM2.5 Chemical Characterization and Source Apportionment after the Implementation of Governmental Measures for Air Pollution Mitigation and Control.

The present study was aimed at determining airborne concentrations of PAHs, Nitro-/Oxy-PAHs and elements in industrial and urban areas of Taranto, a site of environmental risk in Southern Italy, after the issue of strategic measures for air pollution mitigation and control by the Italian Environment Ministry in 2012. A PM2.5 sampling campaign was carried out from 9 to 28 December 2014 at eight receptor sites, two placed in the urban settlement and five included in the high spatial resolution fence monitoring network of the biggest European steel plant. The integration of collected data with meteorological parameters and source apportionment analysis by Positive Matrix Factorization and bivariate polar plots allowed to discriminate among emission sources and estimate their contributions. Evidence on the effect of distinct processes (homogenization, sintering) occurring inside the steel plant on airborne concentrations of PAHs and selected elements was provided. The impact of emissions from the steel plant "core" on the surrounding area was observed at receptor sites downwind to it. Moreover, the extent of the effectiveness of mitigation measures, partially applied at the moment of study's beginning, was demonstrated by mean and peak pollutant concentrations at all receptor sites up to one order of magnitude lower than those documented prior to 2012.

SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy: First evidence.

BACKGROUND: The burden of COVID-19 was extremely severe in Northern Italy, an area characterized by high concentrations of particulate matter (PM), which is known to negatively affect human health. Consistently with evidence already available for other viruses, we initially hypothesized the possibility of SARS-CoV-2 presence on PM, and we performed a first experiment specifically aimed at confirming or excluding this research hyphotesys. METHODS: We have collected 34 PM10 samples in Bergamo area (the epicenter of the Italian COVID-19 epidemic) by using two air samplers over a continuous 3-weeks period. Filters were properly stored and underwent RNA extraction and amplification according to WHO protocols in two parallel blind analyses performed by two different authorized laboratories. Up to three highly specific molecular marker genes (E, N, and RdRP) were used to test the presence of SARS-CoV-2 RNA on particulate matter. RESULTS: The first test showed positive results for gene E in 15 out of 16 samples, simultaneously displaying positivity also for RdRP gene in 4 samples. The second blind test got 5 additional positive results for at least one of the three marker genes. Overall, we tested 34 RNA extractions for the E, N and RdRP genes, reporting 20 positive results for at least one of the three marker genes, with positivity separately confirmed for all the three markers. Control tests to exclude false positivities were successfully accomplished. CONCLUSION: This is the first evidence that SARS-CoV-2 RNA can be present on PM, thus suggesting a possible use as indicator of epidemic recurrence.

Breath Analysis for Early Detection of Malignant Pleural Mesothelioma: Volatile Organic Compounds (VOCs) Determination and Possible Biochemical Pathways.

Malignant pleural mesothelioma (MPM) is a rare neoplasm, mainly caused by asbestos exposure, with a high mortality rate. The management of patients with MPM is controversial due to a long latency period between exposure and diagnosis and because of non-specific symptoms generally appearing at advanced stage of the disease. Breath analysis, aimed at the identification of diagnostic Volatile Organic Compounds (VOCs) pattern in exhaled breath, is believed to improve early detection of MPM. Therefore, in this study, breath samples from 14 MPM patients and 20 healthy controls (HC) were collected and analyzed by Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). Nonparametric test allowed to identify the most weighting variables to discriminate between MPM and HC breath samples and multivariate statistics were applied. Considering that MPM is an aggressive neoplasm leading to a late diagnosis and thus the recruitment of patients is very difficult, a promising data mining approach was developed and validated in order to discriminate between MPM patients and healthy controls, even if no large population data are available. Three different machine learning algorithms were applied to perform the classification task with a leave-one-out cross-validation approach, leading to remarkable results (Area Under Curve AUC = 93%). Ten VOCs, such as ketones, alkanes and methylate derivates, as well as hydrocarbons, were able to discriminate between MPM patients and healthy controls and for each compound which resulted diagnostic for MPM, the metabolic pathway was studied in order to identify the link between VOC and the neoplasm. Moreover, five breath samples from asymptomatic asbestos-exposed persons (AEx) were exploratively analyzed, processed and tested by the validated statistical method as blinded samples in order to evaluate the performance for the early recognition of patients affected by MPM among asbestos-exposed persons. Good agreement was found between the information obtained by gold-standard diagnostic methods such as computed tomography CT and model output.

Airborne Transmission Route of COVID-19: Why 2 Meters/6 Feet of Inter-Personal Distance Could Not Be Enough.

The COVID-19 pandemic caused the shutdown of entire nations all over the world. In addition to mobility restrictions of people, the World Health Organization and the Governments have prescribed maintaining an inter-personal distance of 1.5 or 2 m (about 6 feet) from each other in order to minimize the risk of contagion through the droplets that we usually disseminate around us from nose and mouth. However, recently published studies support the hypothesis of virus transmission over a distance of 2 m from an infected person. Researchers have proved the higher aerosol and surface stability of SARS-COV-2 as compared with SARS-COV-1 (with the virus remaining viable and infectious in aerosol for hours) and that airborne transmission of SARS-CoV can occur besides close-distance contacts. Indeed, there is reasonable evidence about the possibility of SARS-COV-2 airborne transmission due to its persistence into aerosol droplets in a viable and infectious form. Based on the available knowledge and epidemiological observations, it is plausible that small particles containing the virus may diffuse in indoor environments covering distances up to 10 m from the emission sources, thus representing a kind of aerosol transmission. On-field studies carried out inside Wuhan Hospitals showed the presence of SARS-COV-2 RNA in air samples collected in the hospitals and also in the surroundings, leading to the conclusion that the airborne route has to be considered an important pathway for viral diffusion. Similar findings are reported in analyses concerning air samples collected at the Nebraska University Hospital. On March 16th, we have released a Position Paper emphasizing the airborne route as a possible additional factor for interpreting the anomalous COVID-19 outbreaks in northern Italy, ranked as one of the most polluted areas in Europe and characterized by high particulate matter (PM) concentrations. The available information on the SARS-COV-2 spreading supports the hypothesis of airborne diffusion of infected droplets from person to person at a distance greater than two meters (6 feet). The inter-personal distance of 2 m can be reasonably considered as an effective protection only if everybody wears face masks in daily life activities.

Pattern Recognition and Anomaly Detection by Self-Organizing Maps in a Multi Month E-nose Survey at an Industrial Site.

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.

Evaluation of Second-Hand Exposure to Electronic Cigarette Vaping under a Real Scenario: Measurements of Ultrafine Particle Number Concentration and Size Distribution and Comparison with Traditional Tobacco Smoke.

The present study aims to evaluate the impact of e-cig second-hand aerosol on indoor air quality in terms of ultrafine particles (UFPs) and potential inhalation exposure levels of passive bystanders. E-cig second-hand aerosol characteristics in terms of UFPs number concentration and size distribution exhaled by two volunteers vaping 15 different e-liquids inside a 49 m3 room and comparison with tobacco smoke are discussed. High temporal resolution measurements were performed under natural ventilation conditions to simulate a realistic exposure scenario. Results showed a systematic increase in UFPs number concentration (part cm-3) related to a 20-min vaping session (from 6.56 × 103 to 4.01 × 104 part cm-3), although this was one up to two order of magnitude lower than that produced by one tobacco cigarette consumption (from 1.12 × 105 to 1.46 × 105 part cm-3). E-cig second-hand aerosol size distribution exhibits a bimodal behavior with modes at 10.8 and 29.4 nm in contrast with the unimodal typical size distribution of tobacco smoke with peak mode at 100 nm. In the size range 6-26 nm, particles concentration in e-cig second-hand aerosol were from 2- (Dp = 25.5 nm) to 3800-fold (Dp = 9.31 nm) higher than in tobacco smoke highlighting that particles exhaled by users and potentially inhaled by bystanders are nano-sized with high penetration capacity into human airways.

Breath Analysis: A Systematic Review of Volatile Organic Compounds (VOCs) in Diagnostic and Therapeutic Management of Pleural Mesothelioma.

Malignant pleural mesothelioma (MPM) is a rare neoplasm related to asbestos exposure and with high mortality rate. The management of patients with MPM is complex and controversial, particularly with regard to early diagnosis. In the last few years, breath analysis has been greatly implemented with this aim. In this review the strengths of breath analysis and preliminary results in searching breath biomarkers of MPM are highlighted and discussed, respectively. Through a systematic electronic literature search, collecting papers published from 2000 until December 2018, fifteen relevant scientific papers were selected. All papers considered were prospective, comparative, observational case-control studies although every single one pilot and based on a relatively small number of samples. The identification of diagnostic VOCs pattern, through breath sample characterization and the statistical data treatment, allows to obtain a strategic information for clinical diagnostics. To date the collected data provide just preliminary information and, despite the promising results and diagnostic accuracy, conclusions cannot be generalized due to the limited number of individuals included in each cohort study. Furthermore none of studies was externally validated, although validation process is a necessary step towards clinical implementation. Breathomics-based biomarker approach should be further explored to confirm and validate preliminary findings and to evaluate its potential role in monitoring the therapeutic response.

An improved method to determine PM-bound nitro-PAHs in ambient air.

Nowadays, no a standard method for the determination of particulate bound nitro-PAHs (NPAHs) has been developed. Existing methods include complex sampling and extraction procedures. Moreover, their sensitivity does not allow to analyze daily PM10 samples, affecting the temporal resolution of NPAH concentrations. In this study an analytical method for the quantification of NPAHs on half 47 mm-filter samples of daily PM10 was developed and validated. NPAHs were recovered by microwave-assisted extraction, and analyzed by using a gas chromatography-triple quadrupole mass spectrometry in MRM mode. The analytical performance for 14 NPAHs (2-nitrofluorene, 9-nitroanthracene, 9-nitrophenantrene, 3-nitrophenantrene, 2-nitroanthracene, 3-nitrofluoranthene, 1-nitropyrene, 2,7-dinitrofluorene, 7-nitrobenzo[a]anthracene, 6-nitrochrysene, 1,3-dinitropyrene, 1,8-dinitropyrene, 1,6-dinitropyrene, 6-nitrobenza[a]pyrene) was investigated. Recovery extraction percentage exceeded 95% for all target compounds in the range between 0.25 and 10 ng/mL. The repeatability, expressed as Relative Standard Deviation percentage (RSD%) of five determinations, was less than 10% for target compounds except for 2,7-dinitrofluorene, 1,3- and 1,8-dinitropyrene (RSD% < 15%). The limit of detection (LOD) ranged from 12 to 84 pg/mL for most of NPAHs, except for dinitro-pyrenes and nitro-benzo(a)anthracene for which the LOD reached 1.8 ng/mL. The method developed was applied to real samples in order to evaluate the levels of NPAHs in the urban and industrial area of Taranto (South of Italy). The analysis of PM10 samples collected at four industrial and one urban sites, highlighted that in proximity of critical emission source as the biggest European steel plant and under certain weather conditions, combustion processes were the main source of NPAHs in atmosphere.

Carbonaceous PM(2.5) and secondary organic aerosol across the Veneto region (NE Italy).

Organic and elemental carbon (OC-EC) were measured in 360 PM2.5 samples collected from April 2012 to February 2013 at six provinces in the Veneto region, to determine the factors affecting the carbonaceous aerosol variations. The 60 daily samples have been collected simultaneously in all sites during 10 consecutive days for 6 months (April, June, August, October, December and February). OC ranged from 0.98 to 22.34 µg/m(3), while the mean value was 5.5 µg/m(3), contributing 79% of total carbon. EC concentrations fluctuated from 0.19 to 11.90 µg/m(3) with an annual mean value of 1.31 µg/m(3) (19% of the total carbon). The monthly OC concentration gradually increased from April to December. The EC did not vary in accordance with OC. However the highest values for both parameters were recorded in the cold period. The mean OC/EC ratio is 4.54, which is higher than the values observed in most of the other European cities. The secondary organic carbon (SOC) contributed for 69% of the total OC and this was confirmed by both the approaches OC/EC minimum ratio and regression. The results show that OC, EC and SOC exhibited higher concentration during winter months in all measurement sites, suggesting that the stable atmosphere and lower mixing play important role for the accumulation of air pollutant and hasten the condensation or adsorption of volatile organic compounds over the Veneto region. Significant meteorological factors controlling OC and EC were investigated by fitting linear models and using a robust procedure based on weighted likelihood, suggesting that low wind speed and temperature favour accumulation of emissions from local sources. Conditional probability function and conditional bivariate probability function plots indicate that both biomass burning and vehicular traffic are probably the main local sources for carbonaceous particulate matter emissions in two selected cities.

Discontinuous and Continuous Indoor Air Quality Monitoring in Homes with Fireplaces or Wood Stoves as Heating System.

Around 50% of the world's population, particularly in developing countries, uses biomass as one of the most common fuels. Biomass combustion releases a considerable amount of various incomplete combustion products, including particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs). The paper presents the results of Indoor Air Quality (IAQ) measurements in six houses equipped with wood burning stoves or fireplaces as heating systems. The houses were monitored for 48-h periods in order to collect PM10 samples and measure PAH concentrations. The average, the maximum and the lowest values of the 12-h PM10 concentration were 68.6 µg/m³, 350.7 µg/m³ and 16.8 µg/m³ respectively. The average benzo[a]pyrene 12-h concentration was 9.4 ng/m³, while the maximum and the minimum values were 24.0 ng/m³ and 1.5 ng/m³, respectively. Continuous monitoring of PM10, PAHs, Ultra Fine Particle (UFP) and Total Volatile Organic Compounds (TVOC) was performed in order to study the progress of pollution phenomena due to biomass burning, their trends and contributions to IAQ. The results show a great heterogeneity of impacts on IAQ in terms of magnitude and behavior of the considered pollutants' concentrations. This variability is determined by not only different combustion technologies or biomass quality, but overall by different ignition mode, feeding and flame management, which can also be different for the same house. Moreover, room dimensions and ventilation were significant factors for pollution dispersion. The increase of PM10, UFP and PAH concentrations, during lighting, was always detected and relevant. Continuous monitoring allowed singling out contributions of other domestic sources of considered pollutants such as cooking and cigarettes. Cooking contribution produced an impact on IAQ in same cases higher than that of the biomass heating system.

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies.