Arsenic speciation of atmospheric particulate matter (PM10) in an industrialised urban site in southwestern Spain

An arsenic speciation study has been performed in PM10 samples collected on a fortnight basis in the city of Huelva (SW Spain) during 2001 and 2002. The arsenic species were extracted from the PM10 filters using a NH2OH x HCl solution and sonication, and determined by HPLC-HG-AFS. The mean bulk As concentration of the samples analyzed during 2001 and 2002 slightly exceed the mean annual 6 ng m(-3) target value proposed by the European Commission for 2013, arsenate [As(V)] being responsible for the high level of arsenic. The speciation analyses showed that As(V) was the main arsenic species found, followed by arsenite [As(III)] (mean 6.5 and 7.8 ng m(-3) for As(V), mean 1.2 and 2.1 ng m(-3) for As(III), in 2001 and 2002, respectively). The high levels of arsenic species found in PM10 in Huelva have a predominant industrial origin, such as the one from a nearby copper smelter, and do not present a seasonal pattern. The highest daily levels of arsenic species correspond to synoptic conditions in which the winds with S and SW components transport the contaminants from the main emission source. The frequent African dust outbreaks over Huelva may result in an increment of mass levels of PM10, but do not represent a significant input of arsenic in comparison to the anthropogenic source. The rural background levels of arsenic around Huelva are rather high, in comparison to other rural or urban areas in Spain, showing a relatively high atmosphere residence time of arsenic. This work shows the importance of arsenic speciation in studies of aerosol chemistry, due to the presence of arsenic species [As(III) and As(V)] with distinct toxicity.     

Evaluation of artificial neural networks for fine particulate pollution (PM10 and PM2.5) forecasting

Multi-layer perceptron (MLP) artificial neural network (ANN) models are compared with traditional multiple regression (MLR) models for daily maximum and average O3 and particulate matter (PM10 and PM2.5) forecasting. MLP particulate forecasting models show little if any improvement over MLR models and exhibit less skill than do O3 forecasting models. Meteorological variables (precipitation, wind, and temperature), persistence, and co-pollutant data are shown to be useful PM predictors. If MLP approaches are adopted for PM forecasting, training methods that improve extreme value prediction are recommended.     

Anthropogenic and natural influence on the PM(10) and PM(2.5) aerosol in Madrid (Spain). Analysis of high concentration episodes

Non-mineral carbon is the main component of PM10 and PM2.5 at an urban roadside site in Madrid accounting for more than 50% of the total bulk mass in winter pollution episodes. In these cases a 70-80% of the particle mass is anthropogenic. Particles of crustal/mineral origin contribute significantly to the observed PM10 concentrations, especially in spring and summer. They have also been found in the PM2.5 fraction although secondary particles are the next most important contributor in this size. Long-range transport particle episodes of Saharan dust significantly contribute to exceedence of the new daily limiting PM10 value in the urban network and at nearby rural background stations. This type of long-range transport event also influences PM2.5 concentrations. The crustal contribution can account for up to 67 and 53% of the PM10 and PM2.5 bulk mass in such cases.     

南宁市大气颗粒物TSP、PM10、PM2.5污染水平研究

2002年在南宁市的5个典型城市功能区内,共采集了125个大气样品(按季节分别采集),初步调查了大气中颗粒物TSP、PM10、PM2.5的污染状况。结果表明,南宁市TSP、PM10、PM2.5的污染很严重,超标率分别为67．5％、82．5％、92．5％,对人体健康危害更大的PM2．5占到了PM10的63．5％左右。重污染区PM2.5的浓度超过轻污染区近一倍。     

PM10 and PM2.5 source apportionment in the Barcelona Metropolitan area, Catalonia, Spain

Levels of total suspended particles, PM10, PM2.5 and PM1 were continuously monitored at an urban kerbside in the Metropolitan area of Barcelona from June 1999 to June 2000. The results show that hourly levels of PM2.5 and PM1 are consistent with the daily cycle of gaseous pollutants emitted by traffic, whereas TSP and PM10 do not follow the same trend, at least in the diurnal period. The PM2.5/PM10 ratio is dependent on the traffic emissions, whereas additional contribution sources for the >10 μm fraction must be taken into account in the diurnal period. Different PM10 and PM2.5 source apportionment techniques were compared. A methodology based on the chemical determination of 83% of both PM10 and PM2.5 masses allowed us to quantify the marine (4% in PM10 and <1% in PM2.5), crustal (26% in PM10 and 8% in PM2.5) and anthropogenic (54% in PM10 and 73% in PM2.5) loads. Peaks of crustal contribution to PM10 (up to 44% of the PM10 mass) were recorded under Saharan air mass intrusions. A different seasonal trend was observed for levels of sulphate and nitrate, probably as a consequence of the different thermodynamic behaviour of these PM species and the higher summer oxidation rate of SO₂.     

Levels and composition of atmospheric particulates (PM10) in a mining-industrial site in the city of Lavrion,Greece

The present work focuses on the characterization of air quality and the identification of pollutant origin at a former mining site in the city of Lavrion, Greece. A historical metallurgy complex is reused for establishing the Lavrion Technology and Cultural Park (LTCP). A serious problem with this is the severe soil contamination that resulted from intensive mining and metallurgical activities that has taken place in the greater area for the past 3,000 years. Among other consequences, surface-polluted depositions, rich in heavy and toxic metals, are loose and easily wind-eroded, resulting in transportation of particulate matter (PM) in the surrounding atmosphere. On the other hand, there are a number of industries relatively close to the site that are potential sources of PM air pollution. The current study deals with the collection and analysis of PM10 samples with respect to their concentration in heavy metals, such as Pb, Cd, Cu, Fe, Zn, Mn, Cr, and Ni. Though not a heavy metal, As also is included. Furthermore, the source of these elements is verified using statistical correlation and by calculating enrichment factors (EFs), considering that some substances are certainly of contaminated soil origin. Results show that PM10 and element concentrations are relatively low during winter but significantly increase during summer. Fe, Pb, Zn, Mn, and Cu may be considered of contaminated soil origin, while As, Ni, Cd, and Cr are very much enriched with respect to contaminated soil, indicating another possible source attributed to the adjacent industrial plants.     

Elemental characterization of PM10, PM2.5 and PM1 in the town of Genoa (Italy)

The particulate matter (PM) concentration and composition, the PM10, PM2.5, PM1 fractions, were studied in the urban area of Genoa, a coastal town in the northwest of Italy. Two instruments, the continuous monitor TEOM and the sequential sampler PARTISOL, were operated almost continuously on the same site from July 2001 to September 2004. Samples collected by PARTISOL were weighted to obtain PM concentration and then analysed by PIXE (particle induced X-ray emission) and by ED-XRF (energy dispersion X-ray fluorescence), obtaining concentrations for elements from Na to Pb. Some of the filters used in the TEOM microbalance were analysed by ED-XRF to calculate Pb concentration values averaged over 7-30 d periods.     

An integrated approach to identify the origin of PM10 exceedances

Purpose

This study was aimed to the development of an integrated approach for the characterization of particulate matter (PM) pollution events in the South of Italy.

Methods

PM₁₀ and PM_2.5 daily samples were collected from June to November 2008 at an urban background site located in Bari (Puglia Region, South of Italy). Meteorological data, particle size distributions and atmospheric dispersion conditions were also monitored in order to provide information concerning the different features of PM sources.

Results

The collected data allowed suggesting four indicators to characterize different PM₁₀ exceedances. PM_2.5/PM₁₀ ratio, natural radioactivity, aerosol maps and back-trajectory analysis and particle distributions were considered in order to evaluate the contribution of local anthropogenic sources and to determine the different origins of intrusive air mass coming from long-range transport, such as African dust outbreaks and aerosol particles from Central and Eastern Europe. The obtained results were confirmed by applying principal component analysis to the number particle concentration dataset and by the chemical characterization of the samples (PM₁₀ and PM_2.5).

Conclusions

The integrated approach for PM study suggested in this paper can be useful to support the air quality managers for the development of cost-effective control strategies and the application of more suitable risk management approaches.     

应用地质累积指数评价抚顺市PM10中元素的污染

2006-2007年采暖季、风沙季和非采暖季分别在抚顺市的6个采样点采集PM10样品,用等离子体原子发射光谱(ICP-AES)法测定样品中Ti、Al、Mn、Mg、Ca、Na、K、Cu、Zn、As、Pb、Cr、Ni、Co、Cd、Fe、V等17种元素的含量,并用地质累积指数对其污染状况进行初步评价。结果表明:(1)从PM10中元素在不同采样点的含量看,抚顺市PM10中Ti、Mn、Mg、Cu、Zn、Pb、Cr、Ni、Co这9种元素在各采样点间的差别较大;Al、Ca、Na、K、As、Cd、Fe、V这8种元素差别较小。(2)从PM10中元素在不同采样季的含量看,抚顺市PM10中Mn、Mg含量的季间差别较大,其余15种元素季间差别较小。(3)Zn、Cd污染较重;Ti、Al、Mg、Ca、Na、K、As、Fe和V污染较轻;其他6种元素在6个采样点和3个采样季污染程度差别较大。(4)水库采样点各元素污染级别均不是最高;新华采样点PM10中Cu、Zn、Pb、Cr、Ni、Co、Cd污染级别均较高。(5)3个采样季PM10中Cd、Zn污染均较重,属于重度或严重污染;在采暖季PM10中Cu、Pb、Cr的地质累积指数较风沙季、非采暖季大;在非采暖季PM10中Mn、Co受到的污染比采暖季和风沙季稍严重。     

武汉春季大气PM10浓度及有机组成变化特征

采集了武汉春季大气PM10样品,用超声萃取、衍生化、气相色谱/质谱(GC/MS)技术分析了其有机组成.结果表明,PM10质量浓度为160.3～296.7 μg/m3,其夜晚浓度大于白天.PM10中有机物浓度总体表现为正烷酸>左旋葡聚糖>正构烷烃>二元酸>甘油酸酯>多环芳烃>甾醇>藿烷和甾烷的特征,夜晚浓度大于白天,工作日(周一至周五)大于周末(周六、周日).武汉大气颗粒有机物(POM)既有来源于植物蜡等自然源的输入,也有交通和食物烹饪等人为源的影响.     

Wavelet transform-based artificial neural networks (WT-ANN) in PM10 pollution level estimation, based on circular variables

Introduction  

In this paper, a novel method in the estimation and prediction of PM₁₀ is introduced using wavelet transform-based artificial neural networks (WT-ANN).     

Influence of organic and inorganic markers in the source apportionment of airborne PM10 in Zaragoza (Spain) by two receptor models

Improving knowledge on the apportionment of airborne particulate matter will be useful to handle and fulfill the legislation regarding this pollutant. The main aim of this work was to assess the influence of markers in the source apportionment of airborne PM10, in particular, whether the use of particle polycyclic aromatic hydrocarbon (PAH) and ions provided similar results to the ones obtained using not only the mentioned markers but also gas phase PAH and trace elements. In order to reach this aim, two receptor models: UNMIX and positive matrix factorization were applied to two sets of data in Zaragoza city from airborne PM10, a previously reported campaign (2003–2004) (Callén et al. Chemosphere 76:1120-1129, 2009), where PAH associated to the gas and particle phases, ions and trace elements were used as markers and a long sampling campaign (2001–2009), where only PAH in the particle phase and ions were analyzed. For both campaigns, positive matrix factorization was able to explain a higher number of sources than the UNMIX model. Independently of the sampling campaign and the receptor model used, soil resuspension was the main PM10 source, especially in the warm period (21st March–21st September), where most of the PM10 exceedances were produced. Despite some of the markers of anthropogenic sources were different for both campaigns, common sources associated to different combustion sources (coal, light-oil, heavier-oil, biomass, and traffic) were found and PAH in particle phase and ions seemed to be good markers for the airborne PM10 apportionment.     

Characterisation of PM10 atmospheric aerosols for the wet season 2005 at two sites in East Africa

Ambient daily PM₁₀ aerosol samples were collected at two sites in Tanzania in May and June 2005 (during the wet season), and their chemical characteristics were studied. The sites were a rural site in Morogoro and an urban kerbside site in Dar es Salaam. A Gent PM₁₀ stacked filter unit sampler with sequential Nuclepore polycarbonate filters, providing fine and coarse size fractions, and a PM₁₀ sampler with quartz fibre filters were deployed. Parallel collections of 24 h were made with the two samplers and the number of these collections was 13 in Morogoro and 16 in Dar es Salaam. The average mass concentration of PM₁₀ was 27 ± 11 μg/m³ in Morogoro and 51 ± 21 μg/m³ in Dar es Salaam. In Morogoro, the mean concentrations of organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were 6.8, 0.51, and 2.8 μg/m³, respectively. In contrast, higher mean concentrations (11.9, 4.6, and 3.3 μg/m³, respectively) were obtained for Dar es Salaam. At both sites, species and elements, such as black carbon, NH₄⁺, non-sea-salt SO₄^2?, K, and Ni (and at Dar es Salaam also V, As, Br, and Pb) were mainly present in the fine size fraction. The common crustal and sea-salt elements, including Na, Mg, Al, Si, Cl, Ca, Ti, Mn, Fe, and Sr, and also NO₃^? and P (and to a lesser extent Cu and Zn) were concentrated in the coarse particles. Aerosol chemical mass closure indicated that the PM₁₀ mass in Morogoro consisted, on average, of 48% organic matter (OM), 44% crustal matter, 4% sea salt, and 2% EC, while in Dar es Salaam OM, crustal matter, sea salt, and EC represented 37%, 32%, 9%, and 9% of the PM₁₀ mass. The contributions of the secondary inorganic aerosol (non-sea-salt sulphate, nitrate, and ammonium) were small, i.e., only 5% in total at each site. Carbonaceous materials and crustal matter were thus the most important components of the PM₁₀ mass. It is suggested that biomass burning is a major contributor to the OM; at Dar es Salaam there is also a very substantial contribution from traffic. A source apportionment calculation indicated that 68% of the OC at this site originated from traffic exhaust versus 32% from charcoal burning. The crustal matter at Morogoro is likely mainly attributable to soil dust resuspension, whereas in Dar es Salaam it is likely mostly resuspended road dust.     

Analysis of atmospheric aerosol (PM2.5) in Recife city,Brazil

Several studies indicate that mortality and morbidity can be well correlated to atmospheric aerosol concentrations with aerodynamic diameter less than 2.5 µm (PM_2.5). In this work the PM_2.5 at Recife city was analyzed as part of a main research project (INAIRA) to evaluate the air pollution impact on human health in six Brazilian metropolitan areas. The average concentration, for 309 samples (24-hr), from June 2007 to July 2008, was 7.3 µg/m³, with an average of 1.1 µg/m³ of black carbon. The elemental concentrations of samples were obtained by x-ray fluorescence. The concentrations were then used for characterizing the aerosol, and also were employed for receptor modelling to identify the major local sources of PM_2.5. Positive matrix factorization analysis indicated six main factors, with four being associated to soil dust, vehicles and sea spray, metallurgical activities, and biomass burning, while for a chlorine factor, and others related to S, Ca, Br, and Na, we could make no specific source association. Principal component analysis also indicated six dominant factors, with some specific characteristics. Four factors were associated to soil dust, vehicles, biomass burning, and sea spray, while for the two others, a chlorine- and copper-related factor and a nickel-related factor, it was not possible to do a specific source association. The association of the factors to the likely sources was possible thanks to meteorological analysis and sources information. Each model, although giving similar results, showed factors’ peculiarities, especially for source apportionment. The observed PM_2.5 concentration levels were acceptable, notwithstanding the high urbanization of the metropolitan area, probably due to favorable conditions for air pollution dispersion. More than a valuable historical register, these results should be very important for the next analysis, which will correlate health data, PM_2.5 levels, and sources contributions in the context of the six studied Brazilian metropolises.

Implications: The analysis of fine particulate matter (PM_2.5) in Recife city, Brazil, gave a significant picture of the local concentration and composition of this pollutant, which exhibits robust associations to adverse human health effects. Data from 1 year of sampling evaluated the seasonal variability and its connections with weather patterns. Source apportionment in this metropolitan area was obtained based in a combination of receptor models: principal component analysis (PCA)/chemical mass balance (CMB) and positive matrix factorization (PMF). These results give guidelines for local air pollution control actions, providing significant information for a health study in the context of establishing a new national air pollution protocol based on Brazilian cities data.     

Predicting Particulate (PM10) Personal Exposure Distributions Using a Random Component Superposition Statistical Model

ABSTRACT

This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless “attenuation factor” between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM₁₀ measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities.     

Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside

The 24-h average coarse (PM₁₀) and fine (PM_2.5) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM₁₀ and PM_2.5 concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM₁₀ concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM_2.5 concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM₁₀ and PM_2.5 masses showed a high concentration in winter followed by monsoon and summer seasons.The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM₁₀ and PM_2.5 concentrations at the study area. Results indicated that marine aerosol (40.4% in PM₁₀ and 21.5% in PM_2.5) and secondary PM (22.9% in PM₁₀ and 42.1% in PM_2.5) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM₁₀ and 6% in PM_2.5), biomass burning (0.7% in PM₁₀ and 14% in PM_2.5), tire and brake wear (4.1% in PM₁₀ and 5.4% in PM_2.5), soil (3.4% in PM₁₀ and 4.3% in PM_2.5) and other sources (12.7% in PM₁₀ and 6.8% in PM_2.5).     

Characterization of atmospheric PM10 and related chemical species in southern Taiwan during the episode days

The concentrations of atmospheric PM10 on days with episodes of pollution were examined at four different sampling sites (CC, DL, LY, and HK) in southern Taiwan. The related to particulates water-soluble ionic species (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO4(2-)), carbonaceous species (EC and OC) and metallic species (Zn, Ni, Pb, Fe, Mn, Al, Si, V) were also analyzed. On the episode days of this study, the PM10 mass concentration ranged from 155 to 210 microgm(-3), from 150 to 208 microgm(-3), from 182 to 249 microgm(-3), and from 166 to 228 microgm(-3) at CC, DL, LY, and HK, respectively. The results indicate that the dominant water-soluble species were SO4(2-), NO3-, NH4+, and Cl- at the four sampling sites on these days. Moreover, the high sulfate and nitrate conversion values (SOR and NOR) presented herein suggest that secondary formations from SO2 to SO4(2-) and from NO2 to NO3- are present in significant quantities in the atmosphere of southern Taiwan on episode days. In particular, high SOR and NOR verified that both SO4(2-) and NO3- dominated the increase of atmospheric PM10 concentration in southern Taiwan on episode days.     

Ionic composition of PM(10) in the area of Thessaloniki,Greece

Airborne particulate matter (PM(10)) was collected from July 1997 to July 1998 at three locations in the city of Thessaloniki. PM(10) samples were analyzed for Cl(-), NO3(-), SO4(2-), Ca(2+), Mg(2+), Na(+), K(+) and NH4(+). The average PM(10) concentrations were found similar in all three sites with higher values in cold period. The ionic content comprised the 17-23% of the PM(10) mass and sulfate made up the 35-38% of the PM(10) ionic content with an average concentration of 4.80-7.26 microg m(-3). Good correlation was found for SO4(2-) and NO3(-) with Ca(2+), Mg(2+) and Cl(-). Two factors were found to influence the variance of ionic constituents in PM(10) by using factor analysis. Data evaluation considering wind direction showed that higher PM(10) and other ionic concentrations are associated with calm conditions, suggesting influences of local sources.     

Nitrogen isotopes: Tracers of origin and processes affecting PM10 in the atmosphere of Paris

Nitrogen in atmospheric particles in an urban environment is the result of complex primary and secondary processes, which renders identifying its origin somewhat complicated. Using the example of PM₁₀ in the atmosphere of Paris (France), it is shown that the use of stable nitrogen-isotope compositions (δ¹⁵N) alleviates this difficulty and provides clear information on the sources of primary and possibly of secondary nitrogen. Characterization of emissions of the different types of emitters in the city (road traffic, waste incinerators and heating sources) shows that these are clearly discriminated by specific isotope signatures. δ¹⁵N is particularly useful in showing that a substantial portion of the nitrogen is the result of secondary reactions, reactions that are different in summer and winter, as are the corresponding pollution sources. While it is unclear, among point sources, what the winter source of primary nitrogen is, road traffic appear to be the source of primary nitrogen in summer. Identification of the sources of the secondary nitrogen strongly depends on the nitrogen isotope fractionations (Δ¹⁵N) associated to atmospheric conversion of NO_x to nitrate, but hypothesises presented here hint at the possible corresponding pollution sources.     

Source origin of trace elements in PM from regional background,urban and industrial sites of Spain

Despite their significant role in source apportionment analysis, studies dedicated to the identification of tracer elements of emission sources of atmospheric particulate matter based on air quality data are relatively scarce. The studies describing tracer elements of specific sources currently available in the literature mostly focus on emissions from traffic or large-scale combustion processes (e.g. power plants), but not on specific industrial processes. Furthermore, marker elements are not usually determined at receptor sites, but during emission. In our study, trace element concentrations in PM₁₀ and PM_2.5 were determined at 33 monitoring stations in Spain throughout the period 1995–2006. Industrial emissions from different forms of metallurgy (steel, stainless steel, copper, zinc), ceramic and petrochemical industries were evaluated. Results obtained at sites with no significant industrial development allowed us to define usual concentration ranges for a number of trace elements in rural and urban background environments. At industrial and traffic hotspots, average trace metal concentrations were highest, exceeding rural background levels by even one order of magnitude in the cases of Cr, Mn, Cu, Zn, As, Sn, W, V, Ni, Cs and Pb. Steel production emissions were linked to high levels of Cr, Mn, Ni, Zn, Mo, Cd, Se and Sn (and probably Pb). Copper metallurgy areas showed high levels of As, Bi, Ga and Cu. Zinc metallurgy was characterised by high levels of Zn and Cd. Glazed ceramic production areas were linked to high levels of Zn, As, Se, Zr, Cs, Tl, Li, Co and Pb. High levels of Ni and V (in association) were tracers of petrochemical plants and/or fuel-oil combustion. At one site under the influence of heavy vessel traffic these elements could be considered tracers (although not exclusively) of shipping emissions. Levels of Zn–Ba and Cu–Sb were relatively high in urban areas when compared with industrialised regions due to tyre and brake abrasion, respectively.