Biomass burning contributions estimated by synergistic coupling of daily and hourly aerosol composition records

Assessment of seasonal variations in particulate matter accumulation and elemental composition in urban tree species

Outdoor air pollution in urban areas, especially particulate matter (PM), is harmful to human health. Urban trees and shrubs provide crucial ecosystem services such as air pollution mitigation by acting as natural filters. However, urban greenery comprises a particular biodiversity, and different plant species vary in their capacity to accumulate PM. Twenty-two plant species were analyzed and selected according to their leaf traits, the different fractions of PM accumulated on the leaves (large - PML, coarse - PMC, and fine - PMF) and their chemical composition. The study was conducted in four city zones: urban traffic (UT), urban background (UB), industrial (IND), and rural (RUR), comparing winter (W) and summer (S) seasons. The average PM levels in the air and accumulated on the leaves were higher in W than in S season. During both seasons, the highest PM accumulated on the leaves was recorded at the UT zone. Nine species were selected as the most suitable for accumulating PML, seven as the most efficient for accumulating PMC, and six for accumulating PMF. The leaf area and leaf roundness were correlated negatively with PM accumulation. The evergreen species L. nobilis was indicated as suitable for dealing with air pollution based on PM10 and PM2.5 values recorded in the air. Regarding the PM element and metal composition, L. nobilis, Photinia x fraseri, Olea europaea, Quercus ilex and Nerium oleander were selected as species with notable elements and metal accumulation. In summary, the study identified species with higher PM accumulation capacity and assessed the seasonal PM accumulation patterns in different city zones, providing insights into the species interactions with PM and their potential for monitoring and coping with air pollution.

Aerosol characterization and peculiarities of source apportionment in Moscow, the largest and northernmost European megacity

High population and a wide range of activities in a megacity lead to large-scale ecological consequences which require the assessment with respect to distinct characteristics of climate, location, fuel consumption, and emission sources. In-depth study of aerosol characteristics was carried out in Moscow, the largest megacity in Europe, during the cold period (autumn and winter) and in spring. PM10 chemical speciation based on carbonaceous matter, water-soluble ions, and elements was carried out to reconstruct the PM mass and evaluate the primary and secondary aerosol contribution. For the whole study period organic matter, mineral dust, and secondary inorganic/organic accounted for 34, 24, and 16 % of PM10 mass, respectively. PM10, OC, and EC approached a maximum in spring and decreased in winter. Mineral dust seasonal fraction increased from spring (17 %) to autumn (32 %), and then decreased in winter (22 %). Secondary inorganic aerosols (SIA) in opposite showed the maximum 27 % in winter. K+ marked the residential biomass burning in the region surrounding a megacity in spring and autumn, agriculture fires in spring. In winter primary aerosol contribution dropped down 56 % while secondary approached practically equal 44 %. Source factors with the relative contributions are quantified, namely city dust (26 %), traffic (23 %), industrial (20 %), biomass burning (12 %), secondary (12 %), and de-icing salt (7 %); they were significantly varying between the cold heating period and springtime. The relevance of sources to meteorological parameters and mass transportation is investigated by using both bivariate polar plots and Lagrangian integrated trajectory (HYSPLIT) model. Trajectory clustering demonstrates regional sources being crucial contributors to PM10 pollution. Aerosol speciation and source apportion factors identify the differences of the Moscow urban background among large European and Asian cities due to northern climate conditions, fast construction, long-range transport from industrial-developing area surrounding a city, regional biomass burning preferably in spring and autumn, and winter road management.

Multi-class organic pollutants in PM2.5 in mixed area of Shanghai: Levels, sources and health risk assessment

The occurrence of 25 multi-class pollutants comprising phthalate esters (PAEs), polycyclic aromatic hydrocarbons (PAHs), and synthetic musks (SMs) were studied in PM2.5 samples collected at an industrial/commercial/residential/traffic mixed area in Shanghai during four seasons. During the whole period, a slight exceedance of the PM2.5 annual limit was observed, with an average of 36.8 μg/m3, and PAEs were the most predominant, accounting for >70 % of the studied organic pollutants in PM2.5, followed by PAHs and SMs. Statistically significant differences were observed for the concentrations of PM2.5, PAEs, PAHs, and SMs in winter and summer. This seasonal variation could be derived from anthropogenic activities and atmospheric dynamics. Principal component analysis (PCA) and PAHs ratios suggested a mixed source mainly derived from vehicle emissions and industrial processes. Moreover, gaseous pollutants were also accounted for, indicating the emission of PAHs might accompany the NO2 emission process. Finally, inhalation of PM2.5-bound organic pollutants for carcinogenic and non-carcinogenic risks were estimated as average values for each season, showing outside the safe levels in autumn and winter in some cases, suggesting that new policies should be to developed to reduce their emissions and protect human health in this area.

Multi-class organic pollutants in atmospheric particulate matter (PM2.5) from a Southwestern Europe industrial area: Levels, sources and human health risk

The occurrence of 50 multi-class pollutants comprising 18 polycyclic aromatic hydrocarbons (PAHs), 12 phthalate esters (PAEs), 12 organophosphorus flame retardants (OPFRs), 6 synthetic musk compounds (SMCs) and 2 bisphenols was studied in atmospheric particulate matter (PM_2.5) samples collected at an industrial area focused on automotive manufacturing located at the Southwestern Atlantic European region (Vigo city, Spain) during 1-year period. Among all quantitated pollutants in PM_2.5 samples, bisphenol A (BPA) was the most predominant with an average concentration of 6180 pg m^-3, followed by PAHs comprising benzo(b+j)fluoranthene (BbF + BjF) and benzo(g,h,i)perylene (BghiP), accounting for 546 pg m^-3 and 413 pg m^-3 respectively. In addition, two OPFRs concerning tris(chloropropyl) phosphate (TCPP) and triphenyl phosphine oxide (TPPO) were the next following the concentration order, accounting for 411 pg m^-3 and 367 pg m^-3 respectively; being butyl benzyl phthalate (BBP) the most profuse PAE (56.1 pg m^-3 by average). High relative standard deviations (RSDs) were observed during the whole sampling period, while statistically significant differences were only observed for PAHs concentrations during cold and warm seasons. Furthermore, some water-soluble ions and metal(oid)s were analysed in PM_2.5 samples to be used as PM source tracers, whose concentrations were quite below the target levels set in the current legislation. Data obtained from principal component analysis (PCA) and PAHs molecular indices suggested a pyrogenic and petrogenic origin for PAHs, whereas occurrence of the remaining compounds seems to be attributed to resources used in the automotive industrial activity settled in the sampling area. Moreover, although a substantial anthropogenic source to PM_2.5 in the area was observed, marine and soil resuspension contributions were also accounted. Finally, carcinogenic and non-carcinogenic risks posed by PM_2.5-bound pollutants inhalation were assessed, being both averages within the safe level considering the whole period.

Impact of COVID-19 restrictions on the dry deposition fraction of settleable particulate matter at three industrial urban/suburban locations in northern Spain

Ninety 24-h samples of the dry deposition fraction of settleable particulate matter (DSPM) were collected at one suburban industrial site ('EMA') and two urban industrial sites ('Lauredal' and 'Laboratory') in the western area of Gijón (North of Spain) from December 2019 to June 2020. The levels registered point to an environmental issue that should receive close attention from environmental authorities. Before lockdown restrictions due to COVID-19 were established, all samples collected at the EMA site exceeded 300 mg·m^-2·d^-1 (the Spanish limit value until 2002). Large amounts of DSPM were also registered at the Lauredal and Laboratory sites, maximum levels reaching 1039.2 and 672.7 mg·m^-2·d^-1, respectively. Seven metals were analysed in DSPM samples: Al, Ca, Fe, K, Mg, Mn and Na. Fe reached the highest values: 2473.4, 463.4 and 293.3 mg·m^-2·d^-1 (EMA, Lauredal and Laboratory sites, respectively). This study quantifies the reductions in the DSPM levels registered (on average, 97.2, 73.5 and 90.5% at the EMA, Lauredal and Laboratory sites, respectively) during the lockdown, which involved the restriction of population mobility and industrial activity. The influence of wind speed and its direction were also assessed to better understand the role of these restrictions in the observed reductions. The concentrations of all the metals in the DSPM were reduced by more than 75%, on average, except for K at the Laboratory and Lauredal sites. These decreases were much higher than those found by other authors for smaller fractions of the atmospheric particulate matter (PM10, PM2.5). The findings of the present study highlight the importance of DSPM in highly industrialized urban/suburban locations and indicate the direction that legal measures might take, given the influence of anthropogenic emissions.

Spatial distribution and potential sources of arsenic and water-soluble ions in the snow at Ili River Valley, China

Trace elements and water-soluble ions in snow can be used as indicators to reveal natural and anthropogenic emissions. To understand the chemical composition, characteristics of snow and their potential sources in the Ili River Valley (IRV), snow samples were collected from 17 sites in the IRV from December 2018 to March 2019. Inverse distance weighting, enrichment factor (EF) analysis, and backward trajectory modelling were applied to evaluate the spatial distributions and sources of water-soluble ions and dissolved arsenic (As) in snow. The results indicate that Ca²⁺ and SO₄^2- were the dominant ions, and the concentrations of As ranged from 0.09 to 0.503 μg L^-1. High concentrations of As were distributed in the northwest and middle of the IRV, and the concentrations of the major ions were high in the west of the IRV. The strong correlation of As with F^-, SO₄^2-, and NO₂^- demonstrates that As mainly originated from coal-burning and agricultural activities. Principal component analysis showed that the ions originated from a combination of anthropogenic and crustal sources. The EFs showed that K⁺, SO₄^2-, and Mg²⁺ were mainly influenced by human activities. Backward trajectory cluster analysis suggested that the chemical composition of snow was affected by soil dust transport from the western air mass, the unique terrain, and local anthropogenic activities. These results provide important scientific insights for atmospheric environmental management and agricultural production within the IRV.

Low-Cost Air Quality Stations’ Capability to Integrate Reference Stations in Particulate Matter Dynamics Assessment

Low-cost air quality stations can provide useful data that can offer a complete picture of urban air quality dynamics, especially when integrated with daily measurements from reference air quality stations. However, the success of such deployment depends on the measurement accuracy and the capability of resolving spatial and temporal gradients within a spatial domain. In this work, an ensemble of three low-cost stations named “AirQino” was deployed to monitor particulate matter (PM) concentrations over three different sites in an area affected by poor air quality conditions. Data of PM2.5 and PM10 concentrations were collected for about two years following a protocol based on field calibration and validation with a reference station. Results indicated that: (i) AirQino station measurements were accurate and stable during co-location periods over time (R2 = 0.5–0.83 and RMSE = 6.4–11.2 μg m−3; valid data: 87.7–95.7%), resolving current spatial and temporal gradients; (ii) spatial variability of anthropogenic emissions was mainly due to extensive use of wood for household heating; (iii) the high temporal resolution made it possible to detect time occurrence and strength of PM10 concentration peaks; (iv) the number of episodes above the 1-h threshold of 90 μg m−3 and their persistence were higher under urban and industrial sites compared to the rural area.

Concurrent Influence of Different Natural Sources on the Particulate Matter in the Central Mediterranean Region during a Wildfire Season

Wildfire occurrence and severity in the Mediterranean region during the summer season is increasing, being favoured by climate change-induced conditions (i.e., drought, heatwaves). Moreover, additional natural sources frequently impact this region, particularly Saharan dust intrusions. This study focuses on the combined effect of wildfires and Saharan dust on the air quality of the central Mediterranean Basin (CMB) during 2017, an exceptional year for forested burned areas in southern Italy. The annual behaviors of PM2.5, PM10, CO, benzene, and benzo(a)pirene measurements that were recorded at a rural regional-background station located in southern Italy, highlighted a concentration increase during summer. Both Saharan dust and wildfire events were identified while using Navy Aerosol Analysis and Prediction System (NAAPS) model maps, together with high-resolution Weather Research and Forecast—Hybrid Single-Particle Lagrangian Integrated Trajectory (WRF-HYSPLIT) back-trajectories. Additionally, Visible Infrared Imaging Radiometer Suite (VIIRS) satellite detections were considered to establish the enrichment of air masses by wildfire emissions. Finally, the occurrence of these natural sources, and their influence on particulate matter, were examined. In this case study, both PM2.5 and PM10 exceedances occurred predominantly in conjunction with wildfire events, while Saharan dust events mainly increased PM10 concentration when overlapping with wildfire effects.

Chemistry of dry and wet atmospheric deposition over the Balearic Islands, NW Mediterranean: Source apportionment and African dust areas

Wet and dry aerosol deposition samples were collected from September 2010 to August 2012 at a remote background site in the Mallorca Isle (Western Mediterranean). Ions and major and trace elements were determined in soluble and insoluble fractions. Temporal variations of chemical components are discussed and interpreted. The overall pattern associated to long-range-transport air masses is studied: Dry/Wet deposition ratios, charges and composition depend clearly on the meteorological scenario. E.g. Dry/Wet ratio is 1:1 when air comes from North Africa, in contrast to a 1:9 ratio under the mainland Europe influence. Moreover, an innovating source apportionment study was conducted integrating both dry and wet deposition samples. Six sources were revealed, including marine aerosols (32%); two different mineral factors, African dust (15%) and regional dust (12%); two anthropogenic factors, one related to road traffic (8%) and another to regional sources (17%); and a mixed factor having biomass burning emissions and others sources (17%). Temporal variations and influence from long-range-transport air masses are also investigated. Fertilization deposition trends have also been explored, observing nutrients settling, as well as nitrate and sulphate, due to their agricultural interest. An important peak during January-February 2012 is studied in depth. Having in mind the strong impact of African dust on the global deposition budget, the analysis of elemental ratios between key dust components was investigated in order to identify major source areas affecting Western Mediterranean: Western Sahara, Algeria-Hoggar Massif and Tunisia-Libya. Differences among these regions are evident. E.g. the impact of industrial emissions is well-detected under outbreaks from Tunisia-Libya, with relatively high content of Ni and Pb.

Quantifying road traffic impact on air quality in urban areas: A Covid19-induced lockdown analysis in Italy

Covid19-induced lockdown measures caused modifications in atmospheric pollutant and greenhouse gas emissions. Urban road traffic was the most impacted, with 48-60% average reduction in Italy. This offered an unprecedented opportunity to assess how a prolonged (∼2 months) and remarkable abatement of traffic emissions impacted on urban air quality. Six out of the eight most populated cities in Italy with different climatic conditions were analysed: Milan, Bologna, Florence, Rome, Naples, and Palermo. The selected scenario (24/02/2020-30/04/2020) was compared to a meteorologically comparable scenario in 2019 (25/02/2019-02/05/2019). NO₂, O₃, PM_2.5 and PM₁₀ observations from 58 air quality and meteorological stations were used, while traffic mobility was derived from municipality-scale big data. NO₂ levels remarkably dropped over all urban areas (from -24.9% in Milan to -59.1% in Naples), to an extent roughly proportional but lower than traffic reduction. Conversely, O₃ concentrations remained unchanged or even increased (up to 13.7% in Palermo and 14.7% in Rome), likely because of the reduced O₃ titration triggered by lower NO emissions from vehicles, and lower NO_x emissions over typical VOCs-limited environments such as urban areas, not compensated by comparable VOCs emissions reductions. PM₁₀ exhibited reductions up to 31.5% (Palermo) and increases up to 7.3% (Naples), while PM_2.5 showed reductions of ∼13-17% counterbalanced by increases up to ∼9%. Higher household heating usage (+16-19% in March), also driven by colder weather conditions than 2019 (-0.2 to -0.8 °C) may partly explain primary PM emissions increase, while an increase in agriculture activities may account for the NH₃ emissions increase leading to secondary aerosol formation. This study confirmed the complex nature of atmospheric pollution even when a major emission source is clearly isolated and controlled, and the need for consistent decarbonisation efforts across all emission sectors to really improve air quality and public health.

Assessment of major ions and trace elements in snow: A case study across northeastern China, 2017-2018

A total of 60 snow samples from 16 sites across northeastern China were collected from December 2017 to March 2018. The snow samples were analyzed for pH value, major water-soluble ions (Cl^-, NO₃^-, SO₄^2-, Na⁺, NH₄⁺, K⁺, Ca²⁺, and Mg²⁺), and trace elements (Mn, Cr, Cd, Ni, Cu, Zn, Pb, As, and Fe). The results indicated that snow was slightly alkaline (mean pH value 7.54); Ca²⁺ and SO₄^2- were the major ions, contributing up to 33.87% and 22.72% of the major ions, respectively; Pb was the dominant element, contributing up to 62.84% of the trace elements. Both the concentration of major ions and trace elements peaked in the middle or later period of the entire snow season. Enrichment factor (EF) analysis indicated that ions (NO₃^-, NH₄⁺, and Ca²⁺) and trace elements (Pb, As, Cu, and Zn) were severely enriched by anthropogenic activities. Compared with previous studies, which sampled snow from the high altitude and latitude regions, the concentrations of most of the ions and trace elements in this study were found to be 1-3 and 1-4 orders of magnitude higher, respectively, indicating a threat to human health.

Source Apportionment of PM2.5 in Florence (Italy) by PMF Analysis of Aerosol Composition Records

An extensive field campaign was carried out in Florence (Tuscany) to investigate the PM2.5 composition and to identify its sources. The scientific objective of this study is providing a reliable source apportionment, which is mandatory for the application of effective mitigation actions. Particulate matter (PM) was collected for one year, simultaneously in a traffic site, in an urban background, and in a regional background site. While the use of two filter types (quartz and Teflon) allowed obtaining a comprehensive chemical characterization (elemental and organic carbon, ions, elements) by the application of different analytical techniques, the location of the three sampling sites allowed getting a better separation among local, urban, regional and transboundary sources. During shorter periods, the aerosol was also collected by means of a streaker sampler and PIXE (Particle Induced X-ray Emission) analysis of these samples allowed the assessment of hourly resolution elemental time trends. Positive matrix factorisation (PMF) identified seven main sources: traffic, biomass burning, secondary sulphate, secondary nitrates, urban dust, Saharan dust and marine aerosol. Traffic mass concentration contributions were found to be strong only at the traffic site (~8 μg·m−3, 33% of PM2.5). Biomass burning turned out to be an important PM2.5 source in Florence (~4 μg·m−3), with very similar weights in both city sites while at the regional background site its weight was negligible. Secondary sulphate is an important PM2.5 source on a regional scale, with comparable values in all three sites (~3.5 μg·m−3). On average, the contribution of the “natural” components (e.g., mineral dust and marine aerosols) to PM2.5 is moderate (~1 μg·m−3) except during Saharan dust intrusions where this contribution is higher (detected simultaneously in all three sites). High-time resolution data confirmed and reinforced these results.

Chemical Composition of PM10 in 16 Urban, Industrial and Background Sites in Italy

Italy is characterized by a very variable configuration in terms of altitude, proximity to the sea, latitude and the presence of industrial plants. This paper summarizes the chemical characterization of PM10 obtained from 38 sampling campaigns carried out in 16 sites in Italy during the years 2008–2018. Chemical determinations include all macro-components (six macro-elements, eight ions, elemental carbon and organic carbon). The sum of the individual components agrees well with the PM10 mass. The chemical composition of the atmospheric aerosol clearly reflects the variety in the Italian territory and the pronounced seasonal variations in the meteoclimatic conditions that characterize the country. Macro-sources reconstruction allowed us to identify and evaluate the strength of the main PM10 sources in different areas. On 10 sampling sites, the soluble and insoluble fractions of 23 minor and trace elements were also determined. Principal Component Analysis was applied to these data to highlight the relationship between the elemental composition of PM10 and the characteristics of the sampling sites.

Characterization of atmospheric PM2.5 sources at a Central European urban background site

For the purposes of this work, a first in Poland, full-year collection of daily PM_2.5 (particulate matter with aerodynamic diameter smaller than 2.5 μm) samples was chemically analyzed to determine the contents of elemental and organic carbon, water-soluble inorganic ions and 21 minor and trace elements in PM in an urban background site in Warsaw. Annual mean PM_2.5 concentration reached 18.8 μg/m³, with the lowest levels in summer (11.5 μg/m³ on average) and the highest in winter (27.5 μg/m³), with several episodes reaching over 80 μg/m³. Strong seasonal differences were observed mainly for the contents of nitrate and secondary organic carbon (SOC), while sulphate showed the least variability. Secondary species constituted on average 45% of PM_2.5 mass, suggesting large influence of regional and long-range transport of pollutants. Source apportionment with the use of positive matrix factorization (PMF) method, supported by the analysis of enrichment factors, led to identification of six main sources of PM_2.5 origin: residential combustion (fresh & aged aerosol) (46% of PM_2.5 mass), traffic exhaust (21%) and non-exhaust (10%) emissions, mineral dust/construction works (12%), high-temperature processes (8%) and steel processing (3%). Including primary organic carbon (POC) and SOC as two separate constituents helped to distinguish between the primary and secondary sources of the aerosol. The identification of sources was also supported by investigating their yearly and weekly profiles, as well as the correlation of PM constituents with meteorological conditions, which are one of the main drivers of heat generation activities. We found that the most distinctive markers of PM sources in Warsaw are SOC, Cl^- and As for residential combustion, NH₄⁺, Sb and POC for road transport, Ca and Mg for construction works and SO₄^2- for long-range transport of PM.

Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m-3 for PM2.5 and ≈3 µg m-3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m-3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.

Generation of Viable Bacterial and Fungal Aerosols during Biomass Combustion

Biomass combustion is known to be one of the main contributors to air pollution. However, the influence of biomass burning on the distribution of viable bacterial and fungal aerosols is uncertain. This study aimed to examine survivability of bacteria and fungi in the post-combustion products, and to investigate the aerosolization of viable cells during combustion of different types of organic materials. Laboratory experiments included a small-scale combustion of organic materials contaminated with microorganisms in order to determine the survivability of microbes in the combustion products and the potential aerosolization of viable cells during combustion. Field experiments were completed during intentional and prescribed biomass burning events in order to investigate the aerosolization mechanisms that are not available at the laboratory scale. Laboratory experiments did not demonstrate aerosolization of microorganisms during biomass combustion. However, the relatively high survival rate of bacteria in the combustion products ought to be accounted for, as the surviving microorganisms can potentially be aerosolized by high velocity natural air flows. Field investigations demonstrated significant increase in the bioaerosol concentration above natural background during and after biomass combustion.

Biomass burning contribution to PM10 concentration in Rome (Italy): Seasonal, daily and two-hourly variations

The possibility of a relevant contribution of biomass burning for domestic heating to PM₁₀ in the urban area of Rome was explored. The concentration of levoglucosan was determined for 31 months in Rome and in a nearby peri-urban area. During the cold season it reached several hundreds of ng/m³ at both sites, with a clear inverse relationship with air temperature. During the summer it remained well below 100 ng/m³. Although at the peri-urban station the concentration was about 50% higher than at the urban site, the two seasonal patterns show a very good agreement (R² = 0.95), pointing at a main contribution of biomass burning in both areas. Additional information came from the comparison of the 2-h time pattern of levoglucosan and the mixing conditions of the atmosphere, evaluated by monitoring natural radioactivity. During the summer levoglucosan concentration followed the pattern of natural radioactivity, indicating a contribution from many small sources scattered on a wide area (wildfires, barbecues, agricultural fires). During the heating season the activity of a source that switched in the early afternoon and switched off before midnight was highlighted. A 2-h delay between levoglucosan time patterns at the peri-urban and the urban site suggests that biomass burning mainly occurs outside Rome and the combustion products are then transported towards the city centre. Biomass burning contribution to PM₁₀ was estimated as 12% at the peri-urban site and 6.7% inside the city, with relevant implications for the health of the about 2.800.000 citizens living in the urban area of Rome.

Environmental factors affecting the frequency of road traffic accidents: a case study of sub-urban area of Pakistan

Road traffic accidents (RTAs) are among the life-threatening issues facing rural as well as sub-/urban communities. Several factors contribute to RTAs ranging from human to technical and natural/environmental impacts. Anthropogenic air pollution and corresponding environmental factors also increase the probability of RTAs. Current study reports the relationship of the weather conditions to RTAs. The study establishes the relevancy of different weather conditions like rainfall, temperature, fog, and wind storm with the incidences of RTAs in rural and urban settings of Vehari, Punjab-Pakistan. The results of the study showed that rainfall, severe coldness, fog, and heat conditions were directly related with the occurrence of RTAs. The percentage of RTAs which occurred due to fog, rainfall, temperature, and other weather-related factors was 34, 25, 21, and 20%, respectively. The age of the driver significantly correlated (R2 = 0.60) with RTAs; the drivers in the age group 40-60 years caused the least RTAs during their drive. Since the smaller vehicles were involved in maximum RTAs, it relates negatively (R2 = 0.82) to vehicles power. Among different vehicles motor bikes were involved in most (42%) of the reported RTAs. Therefore, during severe weather conditions, vehicles with smaller size and young drivers must be dealt with carefully while interacting (crossing, overtaking, and maneuvering) on the roads regardless of rural or urban conditions. Factors including civic sense, traffic education, vehicle size, drivers' maturity, road conditions, and environmental impacts may be considered while designing traffic rules and traffic aware campaigns specific for developing countries such as Pakistan.

Combined use of daily and hourly data sets for the source apportionment of particulate matter near a waste incinerator plant

A particulate matter (PM) source apportionment study was carried out in one of the most polluted districts of Tuscany (Italy), close to an old waste incinerator plant. Due to the high PM10 levels, an extensive field campaign was supported by the Regional Government to identify the main PM sources and quantify their contributions. PM10 daily samples were collected for one year and analysed by different techniques to obtain a complete chemical characterisation (elements, ions and carbon fractions). Hourly fine (<2.5 μm) and coarse (2.5-10 μm) aerosol samples were collected by a Streaker sampler for a shorter period and hourly elemental concentrations were obtained by PIXE. Positive Matrix Factorization (PMF) analysis of daily and hourly data allowed the identification of 10 main sources: six anthropogenic (Biomass Burning, Traffic, Secondary Nitrates, Secondary Sulphates, Incinerator, Heavy Oil combustion), two natural (Saharan Dust and Fresh Sea Salt) and two mixed sources (Local Dust and Aged Sea Salt). Biomass burning turned out to be the main source of PM, accounting for 30% of the PM10 mass as annual average, followed by Traffic (18%) and Secondary Nitrates (14%). Emissions from the Incinerator turned out to be only 2% of PM10 mass on average. PM10 composition and source apportionment have been assessed in a polluted area near a waste incinerator, by PMF analysis on daily and hourly compositional data sets.

Thin film depth profiling by ion beam analysis

The analysis of thin films is of central importance for functional materials, including the very large and active field of nanomaterials. Quantitative elemental depth profiling is basic to analysis, and many techniques exist, but all have limitations and quantitation is always an issue. We here review recent significant advances in ion beam analysis (IBA) which now merit it a standard place in the analyst's toolbox. Rutherford backscattering spectrometry (RBS) has been in use for half a century to obtain elemental depth profiles non-destructively from the first fraction of a micron from the surface of materials: more generally, "IBA" refers to the cluster of methods including elastic scattering (RBS; elastic recoil detection, ERD; and non-Rutherford elastic backscattering, EBS), nuclear reaction analysis (NRA: including particle-induced gamma-ray emission, PIGE), and also particle-induced X-ray emission (PIXE). We have at last demonstrated what was long promised, that RBS can be used as a primary reference technique for the best traceable accuracy available for non-destructive model-free methods in thin films. Also, it has become clear over the last decade that we can effectively combine synergistically the quite different information available from the atomic (PIXE) and nuclear (RBS, EBS, ERD, NRA) methods. Although it is well known that RBS has severe limitations that curtail its usefulness for elemental depth profiling, these limitations are largely overcome when we make proper synergistic use of IBA methods. In this Tutorial Review we aim to briefly explain to analysts what IBA is and why it is now a general quantitative method of great power. Analysts have got used to the availability of the large synchrotron facilities for certain sorts of difficult problems, but there are many much more easily accessible mid-range IBA facilities also able to address (and often more quantitatively) a wide range of otherwise almost intractable thin film questions.

Regional and long-range transport of aerosols at Mt. Aitana, Southeastern Spain

More than 150 particulate matter (PM) samples with aerodynamic diameters smaller than 1 and 10μm (PM₁ and PM₁₀, respectively) were collected during an 18-month sampling campaign at Mt. Aitana (1558m a.s.l.), located in the western Mediterranean basin. PM samples were analyzed for water-soluble ions, carbonaceous species and trace metals using standard procedures. Average mass concentrations of PM₁ and PM₁₀ were, respectively, 5.0 and 13.3μgm^-3. PM₁ was composed mostly of organic carbon and ammonium sulfate, while nitrate and crustal elements were major components of the PM₁₀ fraction. A significant positive correlation was determined between PM₁₀ and mineral elements such as Ca or Fe. The study of the influence of air mass origin upon PM mass concentrations and composition showed that Saharan dust outbreaks were associated with the highest PM₁₀ levels (24.9μgm^-3 average during African events). Nitrate and crustal components were also considerably increased during these episodes, especially Ti and Fe (~190% higher compared with the average value for the whole study period). The results indicate that Ca/Ti and Ca/Fe ratios can be considered reliable indicators of Saharan dust intrusions.

In-vivo assesment of the genotoxic and oxidative stress effects of particulate matter on Echinogammarus veneris

Seven types of atmospheric dusts (road dust, soil dust, brake dust, desert dust, pellet ash and coke and certified material NIST1648a - urban dust) have been tested for their genotoxicity on specimens of Echinogammarus veneris, a small aquatic amphipod. Experiments were carried out in vivo, by exposing the animals for 24 h to water containing 25 mg/L of dust. Each dust has been chemically analyzed for ions, elemental carbon, organic carbon and for the soluble and insoluble fractions of elements. Non-specific damages to DNA have been evaluated by the comet test, while oxidative damages have been estimated by coupling the comet test with formamido pyrimidine DNA glycosylase reaction. The animal tissues have been acid digested and analyzed for their elemental content to evaluate the bioaccumulation. All the considered dusts have caused a significant non-specific DNA damage, while the oxidative stress was shown only by dust types containing high concentration of elements. Furthermore, the oxidative damage has shown a positive correlation with the total bio-accumulated elemental concentration. For all the dust samples, the correlation with bio-accumulation in the tissues was more satisfactory for the insoluble fraction than for the soluble fraction of elements. Elements contained in solid particles seem then to be the main responsible bioaccumulation and for the oxidative stress.

Spatial and temporal variability of carbonaceous aerosols: Assessing the impact of biomass burning in the urban environment

Biomass burning (BB) is a significant source of atmospheric particles in many parts of the world. Whereas many studies have demonstrated the importance of BB emissions in central and northern Europe, especially in rural areas, its impact in urban air quality of southern European countries has been sparsely investigated. In this study, highly time resolved multi-wavelength absorption coefficients together with levoglucosan (BB tracer) mass concentrations were combined to apportion carbonaceous aerosol sources. The Aethalometer model takes advantage of the different spectral behavior of BB and fossil fuel (FF) combustion aerosols. The model was found to be more sensitive to the assumed value of the aerosol Ångström exponent (AAE) for FF (AAE_ff) than to the AAE for BB (AAE_bb). As result of various sensitivity tests the model was optimized with AAE_ff=1.1 and AAE_bb=2. The Aethalometer model and levoglucosan tracer estimates were in good agreement. The Aethalometer model was further applied to data from three sites in Granada urban area to evaluate the spatial variation of CM_ff and CM_bb (carbonaceous matter from FF or BB origin, respectively) concentrations within the city. The results showed that CM_bb was lower in the city centre while it has an unexpected profound impact on the CM levels measured in the suburbs (about 40%). Analysis of BB tracers with respect to wind speed suggested that BB was dominated by sources outside the city, to the west in a rural area. Distinguishing whether it corresponds to agricultural waste burning or with biomass burning for domestic heating was not possible. This study also shows that although traffic restrictions measures contribute to reduce carbonaceous concentrations, the extent of the reduction is very local. Other sources such as BB, which can contribute to CM as much as traffic emissions, should be targeted to reduce air pollution.

Sources of the PM10 aerosol in Flanders, Belgium, and re-assessment of the contribution from wood burning

From 30 June 2011 to 2 July 2012 PM10 aerosol samples were simultaneously taken every 4th day at four urban background sites in Flanders, Belgium. The sites were in Antwerpen, Gent, Brugge, and Oostende. The PM10 mass concentration was determined by weighing; organic and elemental carbon (OC and EC) were measured by thermal-optical analysis, the wood burning tracers levoglucosan, mannosan and galactosan were determined by gas chromatography/mass spectrometry, 8 water-soluble ions were measured by ion chromatography, and 15 elements were determined by a combination of inductively coupled plasma atomic emission spectrometry and mass spectrometry. The multi-species dataset was subjected to receptor modeling by PMF. The 10 retained factors (with their overall average percentage contributions to the experimental PM10 mass) were wood burning (9.5%), secondary nitrate (24%), secondary sulfate (12.6%), sea salt (10.0%), aged sea salt (19.2%), crustal matter (9.7%), non-ferrous metals (1.81%), traffic (10.3%), non-exhaust traffic (0.52%), and heavy oil burning (3.0%). The average contributions of wood smoke for the four sites were quite substantial in winter and ranged from 12.5 to 20% for the PM10 mass and from 47 to 64% for PM10 OC. Wood burning appeared to be also a notable source of As, Cd, and Pb. The contribution from wood burning to the PM10 mass and OC was also assessed by making use of levoglucosan as single marker compound and the conversion factors of Schmidl et al. (2008), as done in our previous study on wood burning in Flanders (Maenhaut et al., 2012). However, the apportionments were much lower than those deduced from PMF. It seems that the conversion factors of Schmidl et al. (2008) may not be applicable to wood burning in Flanders. From scatter plots of the PMF-derived wood smoke OC and PM versus levoglucosan, we arrived at conversion factors of 9.7 and 22.6, respectively.

Implementing constrained multi-time approach with bootstrap analysis in ME-2: An application to PM2.5 data from Florence (Italy)

Advanced receptor models have been recently developed and tested in order to improve the resolution of apportionment problems reducing rotational ambiguity of results and aiming at identifying a larger number of sources. In particular, multi-time model is a factor analysis method able to compute source profiles and contributions using aerosol compositional data with different time resolutions. Unlike traditional factor analysis, each measured value can be inserted into multi-time model with its original time schedule, thus all temporal information can be effectively used in the modelling process. In this work, multi-time model was expanded in order to impose constraints on modelled factors aiming at improving the source identification. Moreover, as far as we know for the first time, a suitable bootstrap technique was implemented in the multi-time scheme to estimate the uncertainty of the final constrained solutions. These implemented approaches were tested on a PM2.5 (particulate matter with aerodynamic diameter <2.5 μm) dataset composed of 24-h samples collected during one year and hourly data sampled in parallel for two shorter periods in Florence (Italy). The daily samples were chemically characterised for elements, ions and carbonaceous components while elemental concentrations only were available for high-time resolved samples. The application of the advanced model revealed the major contribution from traffic (accounting for 37% of PM2.5 as annual average) and allowed an accurate characterisation of involved emission processes. In particular, exhaust and non-exhaust emissions were identified. The constraints imposed in the continuation run led to a better description of the factor associated to nitrates and also of biomass burning profile and the bootstrap results gave useful information to assess the reliability of source apportionment solutions. Finally, the comparison with the results computed by ME-2 base model applied to daily and hourly compositional data separately demonstrated the advantages provided by the multi-time approach.

Influence of road traffic, residential heating and meteorological conditions on PM10 concentrations during air pollution critical episodes

The importance of road traffic, residential heating and meteorological conditions as major drivers of urban PM10 concentrations during air pollution critical episodes has been assessed in the city of Florence (Italy) during the winter season. The most significant meteorological variables (wind speed and atmospheric stability) explained 80.5-85.5% of PM10 concentrations variance, while a marginal role was played by major emission sources such as residential heating (12.1%) and road traffic (5.7%). The persistence of low wind speeds and unstable atmospheric conditions was the leading factor controlling PM10 during critical episodes. A specific PM10 critical episode was analysed, following a snowstorm that caused a "natural" scenario of 2-day dramatic road traffic abatement (-43%), and a massive (up to +48%) and persistent (8 consecutive days) increase in residential heating use. Even with such a strong variability in local PM10 emissions, the role of meteorological conditions was prominent, revealing that short-term traffic restrictions are insufficient countermeasures to reduce the health impacts and risks of PM10 critical episodes, while efforts should be made to anticipate those measures by linking them with air quality and weather forecasts.