Polycyclic aromatic hydrocarbons in a bakery indoor air: trends, dynamics, and dispersion.

Indoor air pollution assessment in work environments remains challenging due to a combination of logistic reasons and availability of costly instrumentation for data acquisition and post-processing. Existing literature focuses on energy production environments, hospitals, and less so on food production spaces. Studies on indoor air quality in bakeries are scarce or even absent. Motivated by this, the present study investigates indoor air quality in a bakery located in Bari province in South Italy, using a combination of approaches including analytical chemistry analyses and computational fluid dynamics to reconstruct the air ventilation in response to air temperature gradients within the working environment. PM2.5 indoor samplings were collected every 6 h from 7 to 19 April 2013 in the proximity of two bakery ovens powered by gas and wood, respectively. For each sampling day, 4 PM2.5 samples were collected: from 3:00 to 9:00 h (first), from 9:00 to 13:30 h (second), from 14:00 to 21:00 h (third), and from 21:00 to 3:00 h (fourth). In total, 40 samples were collected. On each sample, several polycyclic aromatic hydrocarbons (PAHs) were determined such as benzo[a]anthracene (228), benzo[b]fluoranthene (252), benzo[k]fluoranthene (252), benzo[a]pyrene (252), benzo[g,h,i]perylene (276), indeno[1,2,3-cd]pyrene (276), and dibenzo[a,h]anthracene (278), the main compounds of 16 priority US Environmental Protection Agency (US-EPA) PAHs in particulate phase. The PAH mean concentrations showed higher values during the first (from 3:00 to 9:00 h) and fourth (from 21:00 to 3:00 h) sampling intervals than the other two with benzo[a]pyrene mean values exceeding the Italian law limit of 1 ng/m3. Taking into account benzo[a]pyrene mean concentration for the first interval and the first plus the second one, which are the hours with the largest working activity, we have estimated that the baker and co-workers are exposed to a cancer risk of 4.3 × 10-7 and 5.8 × 10-7, respectively (these values are lower than US-EPA recommended guideline of 10-6). Our study was complemented by numerical analyses using state-of-the-art computational fluid dynamics to reconstruct at high resolution air movement from the various working places, i.e., the bakery and the selling area which were connected via a door. The numerical simulations were possible given that surface temperature using infrared thermography as well as air temperature was continuously recorded throughout the sampling acquisition. The use of this approach allowed us to estimate the transport and diffusion of benzo[a]pyrene from one area to the other thus complementing the point sampling information. Computational fluid dynamic simulation results confirm the presence of benzo[a]pyrene in the laboratory as obtained from the measurements and suggests its presence in the sales' area of the bakery with concentrations similar those found in the laboratory.

Results of an interlaboratory comparison of analytical methods for quantification of anhydrosugars and biosugars in atmospheric aerosol.

An interlaboratory comparison was performed to evaluate the analytical methods for quantification of anhydrosugars - levoglucosan, mannosan, galactosan - and biosugars - arabitol, glucose and mannitol - in atmospheric aerosol. The performance of 10 laboratories in Italy currently involved in such analyses was investigated on twenty-six PM (particulate matter) ambient filters, three synthetic PM filters and three aqueous standard solutions. An acceptable interlaboratory variability was found, determined as the mean relative standard deviation (RSD%) of the results from the participating laboratories, with the mean RSD% values ranging from 25% to 46% and decreasing with increasing sugar concentration. The investigated methods show good accuracy, evaluated as the percentage error (ε%) related to mean values, since method biases ranged within ±20% for most of the analytes measured in the different laboratories. The detailed investigation (ANOVA analysis at p < 0.05) of the contribution of each laboratory to the total variability and the measurement accuracy shows that comparable results are generated by the different methods, despite the great diversity in terms of extraction conditions, chromatographic separation - more recent LC (liquid chromatography) and EC (exchange chromatography) methods compared to more widespread GC (gas chromatography) - and detection systems, namely PAD (pulsed amperometric detection) or mass spectrometry.

Characterising the hydrological regime of an ungauged temporary river system: a case study.

Temporary streams are characterised by specific hydrological regimes, which influence ecosystem processes, groundwater and surface water interactions, sediment regime, nutrient delivery, water quality and ecological status. This paper presents a methodology to characterise and classify the regime of a temporary river in Southern Italy based on hydrological indicators (HIs) computed with long-term daily flow records. By using a principal component analysis (PCA), a set of non-redundant indices were identified describing the main characteristics of the hydrological regime in the study area. The indicators identified were the annual maximum 30- and 90-day mean (DH4 and DH5), the number of zero flow days (DL6), flow permanence (MF) and the 6-month seasonal predictability of dry periods (SD6). A methodology was also tested to estimate selected HIs in ungauged river reaches. Watershed characteristics such as catchment area, gauging station elevation, mean watershed slope, mean annual rainfall, land use, soil hydraulic conductivity and available water content were derived for each site. Selected indicators were then linked to the catchment characteristics using a regression analysis. Finally, MF and SD6 were used to classify the river reaches on the basis of their degree of intermittency. The methodology presented in this paper constitutes a useful tool for ecologists and water resource managers in the Water Framework Directive implementation process, which requires a characterisation of the hydrological regime and a 'river type' classification for all water bodies.

Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites.

In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project "Improvement of the Regional Agro-meteorological Monitoring Network (2004-2007)". LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.

Chemical characterization of biomass fuel particulate deposits and ashes in households of Mt. Everest region (NEPAL).

During a sampling campaign, carried out during June 2012, inside some traditional households located in four villages (Phakding, Namche, Pangboche and Tukla) of Mt. Everest region in southern part of the central Himalaya (Nepal), particulate matter (PM) depositions and ashes have been collected. Moreover, outdoor PM depositions have also been analyzed. Chemical characterization of PM depositions and ashes for major ions, organic carbon, elemental carbon (EC), metal content and PAHs (Polycyclic Aromatic Hydrocarbons) allowed identifying, as major contributes to indoor PM, the following sources: biomass burning, cooking and chimney ashes. These sources significantly affect outdoor PM depositions: in-house biomass burning is the major source for outdoor EC and K+ as well as biomass burning and cooking activities are the major sources for Polycyclic Aromatic Hydrocarbons.

PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set.

BACKGROUND: The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 µm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it's referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). RESULTS: Comparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors.The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants. CONCLUSIONS: The analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant's sources. These knowledge can provide useful advices to environmental policies in order to reach the WHO recommended levels.

Source apportionment of groundwater pollutants in Apulian agricultural sites using multivariate statistical analyses: case study of Foggia province.

BACKGROUND: Ground waters are an important resource of water supply for human health and activities. Groundwater uses and applications are often related to its composition, which is increasingly influenced by human activities.In fact the water quality of groundwater is affected by many factors including precipitation, surface runoff, groundwater flow, and the characteristics of the catchment area. During the years 2004-2007 the Agricultural and Food Authority of Apulia Region has implemented the project "Expansion of regional agro-meteorological network" in order to assess, monitor and manage of regional groundwater quality. The total wells monitored during this activity amounted to 473, and the water samples analyzed were 1021. This resulted in a huge and complex data matrix comprised of a large number of physical-chemical parameters, which are often difficult to interpret and draw meaningful conclusions. The application of different multivariate statistical techniques such as Cluster Analysis (CA), Principal Component Analysis (PCA), Absolute Principal Component Scores (APCS) for interpretation of the complex databases offers a better understanding of water quality in the study region. RESULTS: Form results obtained by Principal Component and Cluster Analysis applied to data set of Foggia province it's evident that some sampling sites investigated show dissimilarities, mostly due to the location of the site, the land use and management techniques and groundwater overuse. By APCS method it's been possible to identify three pollutant sources: Agricultural pollution 1 due to fertilizer applications, Agricultural pollution 2 due to microelements for agriculture and groundwater overuse and a third source that can be identified as soil run off and rock tracer mining. CONCLUSIONS: Multivariate statistical methods represent a valid tool to understand complex nature of groundwater quality issues, determine priorities in the use of ground waters as irrigation water and suggest interactions between land use and irrigation water quality.

Collection and analytical characterisation of the atmospheric particulate in the city of Bari.

In this paper an application of new procedures for atmospheric particulate analysis is illustrated. PM10, PAHs (benzo[a]anthracene (BaA), benzo[b]fluoranthene (BbF), benzo[j]fluoranthene (BjF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), indeno[1, 2, 3-cd]pyrene (Ip), dibenzo[a, h]anthracene (DbA)) and heavy metals (Cu, Ni, Zn, Co, Mn, Cd, Fe and Pb) were investigated. PM10 determination was performed by gravimetric method, PAHs were measured by GC-MS, and heavy metals by HPIC. An air quality monitoring campaign on the territory of Bari municipality has been organised, and its results are shown.