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Chemical characterization of particulate matter (PM) measured along trafficked roads in Chennai city was performed during the winter season. Several heights, from 3 m to about 38 m above the ground level, and road geometries were taken into account. The daily average coarse (PM10) and fine (PM2.5) particles concentrations were in the range 72–110 (for PM10) and 34–57 μg/m3 (for PM2.5), depending on the site. Samples were analyzed in terms of inorganic ions using Ion Chromatography (IC) and elements by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Results indicated the dominance of SO 4 2 − followed by Na + , Ca 2 + , NO 3 − and Cl − ions in the coarse fraction; similarly, in the fine fraction ion concentrations decreased in the following order: SO 4 2 − , NH 4 + , K + and Ca 2 + . Among the elements, crustal element (Al, Fe) and Zn concentrations were much higher (accounting about 90% of the total elemental concentration) than other toxic elements (Cr, Cu, Mn, Ni, Pb, Sn, Ti and V). No element showed a significant dependence on height, expect for calcium at site ‘Velachery’ which contributed significantly to the abundance of the coarse fraction mass. In order to identify the major sources of air pollution, the collected data were analyzed using Positive Matrix Factorization (PMF), allowing to highlight five dominant pollution sources/factors: secondary PM, road traffic, biomass burning, sea spray and crustal erosion. Overall, the present study provided a new insight for the source apportionment of monitored pollutants in the Chennai city.

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.

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.

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%

In recent years, the use of synthetic materials in building and furnishing, the adoption of new lifestyles, the extensive use of products for environmental cleaning and personal hygiene have contributed to the deterioration of indoor air quality and introduced new sources of risk to humans. Indoor environments include home, workplaces such as offices, public buildings such as hospitals, schools, kindergartens, sports halls, libraries, restaurants and bars, theaters and cinemas and finally cabins of vehicles. Indoor environments in schools have been of particular public concern. According to recent studies, children aged between 3 and 14 spend 90 % of the day indoors both in winter and summer. Moreover, children have greater susceptibility to some environmental pollutants than adults, because they breathe higher volumes of air relative to their body weights, and their tissues and organs are actively growing. In this review, the authors explore the methodological approaches used for the assessment of air quality in schools: monitoring strategies, sampling and analysis techniques and summarizing an overview of main findings from scientific literature concerning the most common pollutants found in school environments.

An artificial neural network (ANN) was developed and tested to forecast PM 10 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 PM 10 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 PM 10 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 PM 10 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.

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.

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.

Particulate matter (PM) is a very complex mixture of many inorganic and organic compounds of primary and secondary origin and this is the main reason why the desired reduction of its concentration and the identification of its many sources constitute a very difficult task. It is widely recognised that atmospheric particles are responsible for adverse effects on the ecosystem, the climate and the health of human beings (Pope & Dockery, 2006). Epidemiological studies have shown a consistent association of the mass concentration of urban air thoracic particles (PM10 particles with an aerodynamic diameter smaller than 10 μm), and its sub-fraction fine particles (PM2.5 particles with an aerodynamic diameter smaller than 2.5 μm), with mortality and morbidity among cardio-respiratory patients (WHO, 2005). Recent studies indicate that PM10 is associated to respiratory responses while PM2.5 may contribute to cardiovascular diseases (Wyzga, 2002). The chemical characteristics of the particulate fractions and biological mechanisms responsible for these adverse health effects are still unknown as well as the aerosol parameters (mass, particle size, surface area, etc) involved in the health impacts (Hauck et al., 2004). In addition, there is an indication that the increase in the atmospheric aerosol burden delays the global warming attributed to the increase in greenhouse gasses (GHG: CO2, CH4, N2O, halocarbons). Whether the increase in GHGs since preindustrial times is producing a warming of 2.3 Wm,anthropogenic contributions to aerosols (primarily sulphate, organic carbon, black carbon, nitrate and dust) together produce a cooling effect, with a total direct radiative forcing of -0.5 Wm2 and an indirect cloud albedo forcing of -0.7 Wm (IPCC, 2007). In recent years many studies have been carried out to determine the chemical composition of atmospheric particulate matter (Vecchi et al., 2007). Most of these studies were devoted to the identification of the main particle sources, with the purpose to identify viable strategies for their reduction. In this chapter we focus the attention mostly on the ionic component of