Isolation and characterization of a respirable particle fraction from residential house-dust

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Citation for the original published paper (version of record):

Gustafsson, A., Krais, A M., Gorzsás, A., Lundh, T., Gerde, P. (2018)

Isolation and characterization of a respirable particle fraction from residential house- dust

Environmental Research, 161: 284-290 https://doi.org/10.1016/j.envres.2017.10.049

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Contents lists available atScienceDirect

Environmental Research

journal homepage:www.elsevier.com/locate/envres

Isolation and characterization of a respirable particle fraction from residential house-dust

Åsa Gustafsson

^a,b,⁎

, Annette M. Krais

^a,c

, András Gorzsás

^b

, Thomas Lundh

^c

, Per Gerde

^a,d

aSwetox, Karolinska Institutet, Unit of Toxicology Sciences, Forskargatan 20, SE-151 36 Södertälje, Sweden

bDepartment of Chemistry, Umeå University, Linnaeus väg 6, SE-901 87 Umeå, Sweden

cDivision of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, SE-221 85 Lund, Sweden

dInstitute of Environmental Medicine (IMM), Karolinska Institutet, Box 287, SE-17177 Stockholm, Sweden

A R T I C L E I N F O

Keywords:

Indoor air House dust Respirable Inhalation Health

Particle characterization

A B S T R A C T

Indoor air pollution has caused increasing concern in recent years. As we spend most of our lives indoors, it is crucial to understand the health effects caused by indoor air pollution. Household dust serve as good proxy for accessing indoor air pollution, especially smaller dust particles that can pass into the lungs are of interest. In this study we present an efficient method for the isolation of dust particles in the respirable size range. The respirable fraction was recovered from vacuum cleaner bags, separated by stepwise sieving, followed by characterization for size, morphology, surface area, organic content and elemental composition. The respirable fraction was obtained in a yield of 0.6% with a specific surface area of 2.5 m²/g and a Mass Median Aerodynamic Diameter of 3.73 ± 0.15 µm. Aluminum and zink were the dominating metals measured in the dust, whereas the major mineral components were found to be silicon dioxide and calcium carbonate. The fraction of organic matter in the dust was measured to be 69 ± 1%. The organic matrix contained bacterial and fungi and a presence of skin fragments. We present here an efficient and fast method for the isolation of dust particles in the respirable size range. That is of considerable value due to the need for large quantities of respirable particle fractions to conduct toxicological studies and risk assessment work.

1. Practical implications

More attention should be paid to exposure toﬁne dust particles. In order to perform risk assessment following inhalation of dust particles, it is important to select the relevant size range that is representative for inhalation exposure. Selection of size fraction may also aﬀect the ac- curacy of assessing human exposure to indoor pollutants, such as semi volatile organic compounds that adsorb at surfaces such as the dust and the health impact thereof.

2. Introduction

The U.S. Environmental protection agency (US EPA) and U.S.

Centers for disease control (CDC) have evaluated the quality of the indoor environment, ranking indoor air pollution as a high environmental risk (Butte and Heinzow, 2002). Over the last years the pre- valence of common diseases such as cancer, diabetes, neurological disorders and infertility have increased. As we spend most of our lives indoors, there could be a correlation with pollutants from indoor air and household dust (Diamanti-Kandarakis et al., 2009; Meeker, 2012).

Indoor environments are largely inﬂuenced by outdoor sources, but are also dependent on indoor activities such as heating, cooking, cleaning and not at least by the use of numerous consumer products and different types of building materials, including e.g:ﬂame retardants and plasticizers (Butte and Heinzow, 2002; Morawska et al., 2013). The composition of dust particles depends largely on their sources (Abt et al., 2000). Household dust is a heterogeneous material consisting of inorganic metals and minerals, as well as organic contents such as hair, dead skin cells, pollen and a diversity of microorganisms (Betts, 2008;

Lewis et al., 1999; Mølhavea et al., 2000; Owen and Ensor, 1992).

House dust act as a repository for various compounds with origin from both indoor and outdoor environment (Butte and Heinzow, 2002). Dust is thus an important environmental matrix with respect to human exposure. Therefore a comprehensive characterization of the house dust composition is important to investigate in order to understand impacts from dust exposure on human health (Rager et al., 2016). Humans are constantly exposed to dust particles via multiple routes and the exposure pathway occur via ingestion, skin and by inhalation (Blanchard et al., 2014; Mercier et al., 2011; Weschlera and Nazaroﬀ, 2008). The airways as a route of exposure to the particulate matrix from indoor

http://dx.doi.org/10.1016/j.envres.2017.10.049

Received 3 September 2017; Received in revised form 27 October 2017; Accepted 28 October 2017

⁎Corresponding author at: Swetox, Karolinska Institutet, Unit of Toxicology Sciences, Forskargatan 20, SE-151 36 Södertälje, Sweden.

E-mail address:asa.gustafsson@swetox.se(&. Gustafsson).

Available online 21 November 2017

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environment is poorly explored. Our lungs are in contact with considerable amounts of dust every day, considering a daily inhalation volume of 10 000 L (Tsuda et al., 2013), and an average concentration of particulate matter (PM2.5) ranging from 10.6 to 54 µg/m3 of air as measured by personal monitoring (Morawska et al., 2013). Health effects may arise not only from oxidative stress and inﬂammatory processes (Falcon-Rodriguez et al., 2016), but also due to dust particles acting as carrier vehicles for numerous semi volatile organic chemical compounds (Blanchard et al., 2014; Weschlera and Nazaroﬀ, 2008).

Airborne particles may interfere with the airways and will deposit in diﬀerent regions of the airways, depending on their aerodynamic properties. The parameter most closely linked to airway deposition properties of particles is the aerodynamic diameter, which is the diameter of a unit density sphere, displaying the same deposition behavior as the studied particle. Generally, larger particles, with a diameter between 5 and 10 µm deposit primarily in the extrathoracic airways;

particles between 1 and 5 µm diameters mostly deposit in the tracheo- bronchiol region; whereas particles with diameters below 1 µm commonly deposit in the alveolar region with considerable overlaps (Owen and Ensor, 1992; Oberdörster et al., 2005).

To fully understand the potential health eﬀects of inhalational exposure to household dust, it is crucial to achieve a more complete characterization of the respirable dust fraction. The objective of this study was to develop a method for fractionating dust in the respirable size range and to perform a physical and chemical characterization of the respirable size fraction of house dust.

In this study we present a fast method in which the isolation of dust particles in the respirable size range is achieved with high yield. Such a method is crucial when evaluating the possible health hazards of the respirable sized particles in house dust and it may be a valuable tool for improving risk assessments of indoor environments in the future.

3. Material and methods 3.1. Collection of house dust

The house dust was acquired through active sampling of the home environments by the normal use of vacuum cleaning, exercised by household residents. There were no prescribed instructions to the vacuum cleaner users of the residences who volunteered. Vacuum cleaner bags were collected from households in the cities of Stockholm and Södertälje in Sweden during the autumn of 2015. The vacuum cleaner bags where stored in black plastic bags in the dark at the temperature of 21 °C and a relative humidity of 20–30% until the sieving process started. In total thirty-two vacuum cleaner bags yielded a total mass of 5925 g household dust.

3.2. Sieving of house dust

In order to separate the respirable size fraction, the house dust was processed in two steps. A schematic description is presented inFig. 1. In step 1, the vacuum cleaner bag was cut up with a scissor and the dust was removed with an industrial vacuum cleaner (Dustcontrol 2500, Norsborg, Sweden) at aflow of approximately 30 l per s. Consecutively, the house dust was drawn through a staple of six wood boxes, each containing a stainless steel mesh at the bottom. The stainless mesh (plane weave) -dimensions were: 2000 µm, 1000 µm, 390 µm (AISI 316, Stockholms Plåt och Gummiperforering SPG AB, Västerhaninge, Sweden) followed by meshes of 190 µm, 75 µm and 25 µm, all plain weave (SS 2343, Silduksfabriken in Jönköping AB, Tenhult, Sweden). In order to obtain a better yield the house dust was gently brushed back and forth on each mesh using afine hair paintbrush to de-agglomerate the dust. Following the last mesh, via a plastic funnel, the dust entered an ash cyclone (Virvelvind, Pellvac AB, Strömsnäsbruk, Sweden) connected with a polypropylene tube with a 45 mm diameter (Krauta, Sweden). After the cyclone the dust continued into a HEPA filter

container (Clas Ohlson, Sweden) in which thefine size fraction was collected in afilter bag (Swirl M50, Melitta Nordic AB, Helsingborg, Sweden). The cyclone and filter container were connected with a polypropylene tube of 45 mm diameter (Krauta, Sweden). Each house dust fraction was transferred to pre weighed glass bottles and stored in the dark. The dust collected in the vacuum cleaner bag was removed by extraction using a vacuum pump (Becker, Germany) on to a nylon membranefilter (0.45 µm, NY4514225, Sterlitech, WA, USA) placed in an aluminumfilter holder. From that filter the dust was gently removed with a brush and collected in a glass vial.

A schematic description is presented in Fig. 1. Step 2. A small amount of house dust from step 1 was dispersed on a twilled weave mesh 25 µm (Silduksfabriken in Jönköping AB, Tenhult, Sweden) and drawn on to a subsequent 6 µm nylon mesh (Nitex 03 6/5, Sefar AG, Heiden, Switzerland) using an industrial vacuum cleaner described in step one. In order to obtain a larger yield the house dust was gently brushed back and forth for further de-agglomeration. Dust collected on the nylon mesh was removed by extraction with a vacuum pump (Becker, Germany) on to a nylon membrane ﬁlter (0.25 µm, NY4514225, Sterlitech, WA, USA) placed in an aluminumﬁlter holder.

From theﬁnal ﬁlter the dust was gently removed by brushing into a glass vial. Before the physical and compositional characterization of the dust it was homogenized by rotation of the glass vial overnight. For all analyses only one replicate was used, except for determination of dry matter- and ignition residue where three replicates were used.

3.3. Physical characterization of the house dust

3.3.1. Size distribution of the house dust

The size distribution of the house dust was determined using a cascade impactor (Marple Andersen, EnVirREC AB, Sweden). The house dust was aerosolized with the PreciseInhale system (Inhalation Sciences Sweden AB, Stockholm, Sweden) and the aerodynamic size distribution of the dust was determined with the cascade impactor at aﬂow rate of 2 l/min as previously described (Selg et al., 2010, 2013). The mass of dust deposited on the nine stages in the impactor was used to calculate the mass median aerodynamic diameter (MMAD) and the geometric standard deviation (GSD).

3.4. Scanning electron microscopy (SEM)

The house dust particle size, morphology and tendency to agglomerate was characterized byﬁeld emission scanning electron microscopy (SEM; Carl Zeiss Merlin) using a backscatter electron detector at ac- celerating voltage of __ kV and probe current of __ pA (the values can be seen on the data bar of the taken images).

3.5. Surface area

The speciﬁc surface area of the house dust was determined with the Brunauer-Emmett-Teller (BET) method by employing a Micrometrics ASAP2020 volumetric adsorption analyzer. The sample was treated under vacuum conditions at a temperature of 60 ̊C for 10 h. Nitrogen adsorption-desorption isotherms were recorded at liquid-nitrogen temperature (77 K) for the dust sample. The speciﬁc surface areas of the adsorbent dusts were then calculated, according to the BET method, from the recorded data in the range of P/P0=0.05–0.15.

3.6. Composition of the house dust

3.6.1. Determination of dry matter- and ignition residue

Three replicates of house dust samples were analyzed for dry matter residue and organic matter content by ignition residue, conducted according to standardized procedures in SS 028113 (SIS, Swedish Standards Institute, 1981).

&. Gustafsson et al. Environmental Research 161 (2018) 284–290

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3.7. Metal determination by ICP-MS

Dust was analyzed for aluminum (Al), arsenic (As), beryllium (Be), bismuth (Bi), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), manganese (Mn), nickel (Ni), rubidium (Rb), strontium (Sr), thallium (Tl), uranium (U), vanadium (V) and zinc (Zn). About 10 mg dust was added to 10 ml nitric acid (2% v/v). After centrifugation the metal concentrations were determined by inductively coupled plasma- mass spectrometry (ICP-MS; iCAP Q, Thermo Scientiﬁc, Bremen, GmbH) in collision cell mode with kinetic energy discrimination using helium as collision gas. The detection limits calculated as three times the standard deviation of the blank were 0.01 µg/L (Bi, Cd, Co, Rb, Tl, V, U), 0.02 µg/L (As, Cr, Ni, Pb), 0.05 µg/L (Be, Pb), 0.14 µg/L (Cu), 0.22 µg/L (Al) and 0.35 µg/L (Zn).

3.8. Elemental composition determined by X-ray powder diﬀraction (XRD) X-ray powder diﬀraction (XRD) analyzes was performed to determine the main mineral crystalline composition of the house dust.

XRD patterns were collected using a Panalytical Xpert X-ray dif- fractometer equipped with a conventional X-ray tube and a position sensitive detector Xcelerator from which the scattering patterns were recorded as a function of scattering direction. The dust was added by back-loading procedure in a cup to a level of about 2 mm. Theflattened surface of the dust was irradiated with a CuKα radiation source (wa- velength = 1.54 Å). To identify the different components of the dust sample the database PDF4 from International Centre for Diffraction Data (ICDD) has been used. Finally, in order to minimize the difference between the experimental pattern (observed data) and the hypothesized crystal structure of the model and instrumental parameters (calculated pattern) a so-called Rietveld refinement was made using FullProf.

3.9. Elemental composition determined by X-ray photoelectron spectroscopy (XPS)

XPS analysis was performed to determine the elemental composition of the outer surfaces layers of the dust. The XPS spectra were collected with a Kratos Axis Ultra DLD electron spectrometer using mono- chromated Al Kα source operated at 150 W. Analyzer pass energy of 160 eV for acquiring wide spectra and a pass energy of 20 eV for in- dividual photoelectron lines were used. The surface potential was

stabilized by the spectrometer charge neutralization system. The binding energy (BE) scale was referenced to the C 1 s line of aliphatic carbon, set at 285.0 eV. Processing of the spectra was accomplished with the Kratos software.

Powder sample of“home dust” for the analysis were gently hand- pressed into a pellet directly on a sample holder using clean Ni spatula.

3.10. Determination of microorganisms in the house dust

The determination of both bacteria and fungi in the house dust sample were performed by Eurofins Pegasuslab AB (Uppsala, Sweden) according to standard procedures. Briefly; the species taxonomically determination (PSMB12B) was done according to von Arx and Bergey's systematics (von Arx, 1981; Bergey et al., 1974). The determination of cultivable bacteria and fungi (CFU g−1) was performed according to the method based on (Jensen, 1962), and for the determination of total number of bacteria and fungi (PSMB13) the methods was with some modification based on the methods found in (Hobbie et al., 1977;

Trolldenier, 1973; Zimmerman and Meyer-Reil, 1974).

3.11. Determination of organic material with Fourier transform infrared spectroscopy (FTIR)

The determination of organic material consisting of human skin in the dust sample was performed by FTIR. As a reference control, human skin was rubbed oﬀ from the palm and collected in a glass vial. Approx.

5–10 mg of dry dust was mixed with 390 mg of KBr and manually ground using agate mortar and pestle. Spectra were collected according to Gorzsás and Sundberg (Gorzsás and Sundberg, 2014), in diﬀuse re- ﬂectance mode on a Bruker IFS 66/v spectrometer under vacuum conditions (4 mbar), using manually ground pure KBr for background.

A total of 128 interferograms were co-added to obtain high signal-to- noise ratio. A spectral resolution of 4 cm⁻¹and a zeroﬁlling factor of 2 were used and spectra were recorded over the region of 400 – 4000 cm⁻¹. The entire spectral region was used in comparing the samples.

Prior to data evaluation, spectra were preprocessed using the built- in options of OPUS (version 7, Bruker Optics GmbH, Ettlingen, Germany): 64-point rubber band baseline correction and vector (total area) normalization over the entire spectral range. Processed spectra were exported as Matlab (version 2015b, Mathworks Inc. CA, USA) mat Fig. 1. A schematic description of the sieving process of step 1 and 2.

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ﬁles for data logistic and spectral printing.

4. Results & discussions

In order to assess the health effects of inhalational exposure to air pollution particles it is necessary to fully characterize the particles in the respirable size range. A comprehensive investigation of the particles usually requires a lot of material so the collection system for the respirable particle fraction must be highly efficient. In this study we de- scribe an effective method for extracting a respirable fraction of house dust from vacuum cleaner bags. Using vacuum cleaner bags from residential households is an easy and low cost method for sampling large quantities of house dust. Dust could also be sampled using a passive sampling method, where dust is collected by passive dust settling on dishes. The drawback with passive sampling is the scarce quantity of dust that is obtained over a reasonable time (Butte and Heinzow, 2002;

Mercier et al., 2011). In this study we pooled each size fractions from all vacuum cleaner bags in order to obtain a homogeneous batch of house dust containing a larger quantity of particles in the respirable size range. A disadvantage with using vacuum cleaner bags for processing to the respirable fraction of particles is that this small size range might not be completely trapped by the vacuum cleaner bag. The efficiency of trapping the smallest dust size fraction may differ between brands of vacuum cleaner bags. In this study the vacuum cleaner bags varied between households and no information on the particle size separation properties of the vacuum cleaner bags was available. However, most modern vacuum cleaners have a rather small HEPA filter located downstream of the larger dust bag. Thesefilters usually last for quite a while before building pressure drop from collecting the finer size fractions that may escape dust bag, indication a rather high separation efficiency of respirable particles. In addition, while collecting dust over time thefilter bag walls will build an upstream bed of dust potentially increasing the chance small particle collection. An additional thought may be that the processing of dust from vacuum cleaner bags to a respirable fraction may alter the properties of agglomeration compared to thefloating dust that is inhaled indoor. This might result in an over- representation of larger size fractions in our experiments (due to agglomeration) than the“native” particle size of the floating dust before it enters the vacuum cleaner. Nevertheless, when larger quantities of a near respirable dust fraction is needed for chemical analyses of ad- sorbed organic chemicals this processing of house dust from vacuum cleaner bags should be a valuable alternative.

All 32 vacuum cleaner bags with house dust yielded 37 g (0.6%) of dust particles in the respirable size range. The mass and yield from all size fractions are presented in Fig. 2. Previous studies have used methods that sieve crude house dust to obtainﬁner particle size fractions (see Butte et al., and references therein), but few studies have achieved a dust fraction that is in the respirable size range. This sieving method demonstrates to be 300 times more eﬃcient compared to a previous study (Lewis et al.) where a respirable fraction < 4 µm was

processed from vacuum cleaner bags with a yield of 0.002%. Though, this efficiency may also be related to other factors like differences in the environment and properties of the dust. Their method included different stages of sieving followed by a 3.5 µm cyclone, from which the dust were sampled ontofilters (Lewis et al., 1999). Cao et al. used steel meshes in different sizes to sieve house dust from vacuum cleaner bags with a yield of 29.3% of the fraction below < 75 µm (Cao et al., 2013), while our method presented a yielded of only 19.6% for the same size fraction. This discrepancy in yield might be due to the location of dust collection. Cao et al. sampled the dust in offices in Beijing, China, where air pollution levels are generally much higher compared to Stockholm, Sweden.

Following aerosolization the respirable dust fraction produced in our study was measured to be 3.73 ± 0.15 µm MMAD with a GSD of 2.29 ± 0.03 (Fig. 3). The speciﬁc surface area of the same size fraction in bulk was 2.5 m²/g dust (Table 1). Cao et al. used a sedimentation method to obtain fractions in a wider size interval of dust by collecting multiple fractions below < 50 µm. The smallest size fraction collected was measured to be 5.64 ± 6.78 µm, with a surface area of 4.9 m²/g dust (Cao et al., 2013). Compared to our dust, Cao et al., obtained a dust with a larger surface area (4.9 m²/g) despite occupying a larger size interval (5.64 ± 6.78 µm). One explanation could be that smaller particles may be clustered into larger dust agglomerates that are not de- agglomerated in the measurements of the size distribution.

According to SEM images (Fig. 4A and B), the respirable dust fraction was found to be heterogeneous, containing largerﬂakes (with a diameter of more than 20 µm) as well as smaller particles adhered to them. Similar SEM pictures with small particles adhered to largerﬂakes was shown by Cao and colleagues (Cao et al., 2013).Fig. 4B illustrates an image on the house dust particles after aerosolization with the PreciseInhale system. In both pictures (Fig. 4A and B), an agglomeration of house dust particles was clearly visible. During the sieving process, the use of a hair paintbrush was crucial for the dust to be

Fig. 2. Yield of house dust from each sieving fraction in percentage of mass (g).

Fig. 3. Size distribution (mean ± SD, n = 3) of the respirable fraction of house dust following aerosolization of the dust.

Table 1

Physical determination of the respirable fraction of house dust.

Target analyses

MMAD^a(µm) 3.73

GSD^b 2.29

Surface area (m²/g) 2.5

Dry matter residue (%)^c 96 ±

0

Ignition residue of dry matter (%)^c 69 ±

1

aMass median aerodynamic diameter.

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drawn through the steel mesh. Although, de-agglomeration of the dust was achieved by this method, it is possible that the strong van der Waal forces induce an agglomeration upon collection in the ﬁlter bags. So depending on how strong this agglomeration mechanism is compared to the paintbrush de-agglomeration, this may shift the size distribution of the collected particles. However, strong van der Waals forces in the smallest size fractions may indicate that the concentration of particles

< 1 µm will be underestimated. It is also possible that the mechanical de-agglomeration may not simply reverse the previous agglomeration process, resulting in particle breakage producing partly diﬀerent size fractions of small particles. On the other hand, the consistency of composition of the dust over the size fractions seems to be rather stable.

Although particles in the smaller size range possess a lower mass, this fraction consisted of a large number of particles with an increased surface area to weight ratio than larger particles (Butte and Heinzow, 2002; Morawska et al., 2013). This condition was conﬁrmed by Cao et al., who showed that surface area per mass of house dust increased with decreasing dust particle size (Cao et al., 2013).

Mineral dust is produced by natural- or artiﬁcial processes such as weathering or grinding, respectively. Most of these mineral and metal contents are formed outdoors and then enter the homes through ven- tilation or open windows (Owen and Ensor, 1992), or via the household residents. We therefore analyzed the respirable particle fraction for composition, metal content as well as biologic organisms.

The portion of organic matter within the respirable fraction was measured to 69 ± 1% (mean organic matter: 692 mg/g house dust, n = 3) by the loss on ignition of dry matter. The water content in the dust was measured to be 4%. In Danish oﬃces the organic matter and water content were measured to be 33% and 2% respectively (Mølhavea et al., 2000). According to the literature the organic matter in house dust may vary between 5% and 95% (Butte and Heinzow, 2002).

The mineralogical and chemical composition of the respirable house dust fraction was determined by XRD. The main mineralogical components in the dust were analyzed as silicon dioxide (quartz) and calcium carbonate (calcite), both abundant minerals in the Earth's crust.

Their presence in dust was conﬁrmed earlier by a Danish study, ana- lyzing house dust from Danish oﬃces (Mølhavea et al., 2000).

The elemental composition of the outer surface layer of the dust determined by XPS consisted of 78% of carbon, 15.7% of oxygen, and 2.4% of nitrogen (Fig. 5). The inorganic part of the sample included sodium, calcium, potassium, silica, sulfate, aluminum, and chlorine.

The main element found was silicon that is having characteristic binding energies for silicates or alum silicates. Metal analysis using ICP- MS could conﬁrm these ﬁndings. Aluminum was found to be the most abundant metal with a concentration of 2.96 µg/mg dust, followed by Zn (0.80 µg/mg), Cu (0.12 µg/mg), Mn (0.10 µg/mg), Pb (0.04 µg/mg), Sr (0.05 µg/mg), Ni (0.02 µg/mg), Cr (0.02 µg/mg), and Rb (0.01 µg/

mg). The concentrations of metals in indoor dust from Stockholm households are summarized inTable 2together with a comparison to published data. Overall, aluminum is present in the highest concentration, although the concentrations found in Stockholm (2.96 µg/

mg dust) is much lower compared to Tucson, Arizona (7.408 µg/mg

dust) (Beamer et al., 2012), Ottawa, Canada (24.281 µg/mg dust) (Rasmussen et al., 2001), and Birmingham, UK (7.950 µg/mg dust) (Turner and Simmonds, 2006). Internal sources of aluminum include talc and paints, but it may be transported into the house by its occu- pants and by the atmosphere as it is commonly present in garden soil (Turner and Simmonds, 2006). The concentrations of heavy metals (Zn, Cu, Mn, Pb, Ni and Cr) in household dust within the Stockholm region were generally lower than those measured in other cities (Table 2).

High levels of heavy metals in the blood stream are of concern for human health (Baltrusaitis et al., 2012). Trace elements that might impact human health are arsenic (As), beryllium (Be), cadmium (Cd), cobalt (Co), chromium (Cr), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), antimony (Sb), and selenium (Se). Of these Hg, Pb, Se, Mn, and As are elements known to aﬀect the central nervous system (Zevenhoven and Kilpinen, 2005; Normandin et al., 2002). Following airborne exposure, both Pb and Mn are easily absorbed from the lung.

Due to their long-lasting neurological toxicity and peradventure irre- versible eﬀects they are of particular concern (Neal and Guilarte, 2013).

Additionally, Mn has also been proven to migrate the olfactory nerve and pass the blood-brain-barrier, making it of particular concerns for toxicity to the brain (Fechter et al., 2002). Elements that are known to be toxic to the kidneys or liver include Hg, Pb, Se, Cd, and Cu, whereas Ni, Sb, Cd, Se, Cu, Cr are elements associated with toxicity aﬀecting skin, bones or teeth (Zevenhoven and Kilpinen, 2005).

The total number of bacteria and fungi in the house dust sample were 3.2 × 10⁸/g and 6.6 × 10⁷/g, respectively. Out of these < 1% of the bacteria (2.4 × 10⁶CFU g⁻¹) and 1% of the fungi (6.6 × 10⁷CFU g⁻¹) were considered as possible to cultivate. The normal concentration of total cultivable bacteria in dust from residential homes range from ten to 2 × 10⁷CFU g⁻¹and for fungi the concentration can vary between few hundreds to tens of millions, with a mean concentration between 10⁴and 10⁵CFU g⁻¹(Rintala et al., 2012). Theseﬁndings indicate that the microbial content in the respirable size range of dust from the Stockholm region is quite high. It is unknown to which extent the storage of the house dust may have contributed to microbial Fig. 4. Scanning electron microscopy (SEM) images from the total batch (A) and following aerosolization with the PreciseInhale system (B).

Fig. 5. Surface elemental composition of the house dust presented as atomic concentration in percentage (%).

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growth. However, to minimize available humidity the house dust samples were kept in glass bottles under dry and dark conditions. The microbial strains that were detected within the dust have all been identiﬁed in house dust before. The bacteria Bacillus mycoides was found in airborne dust sampled in Sweden. Among the fungi, Aspergillus niger, Aspergillus ochraceus grp., Black-Yeast, Cladosporium, Eurotium, Penicillium chrysogenum, Penicillium spp, Rhizopus, and Ulocladium were detected in the respirable fraction of house dust from the Stockholm region. The most commonly isolated genera from general house dust are Penicillium, Aspergillus and Cladosporium (Rintala et al., 2012;

Nilsson et al., 2004).

Another constituent of the organic matter are dandruﬀs and skin fragments that are continuously shed from animals and humans (Després et al., 2012). In this study FTIR was used to demonstrate such a content in the respirable fraction of house dust. The spectral band shapes from house dust and human skinﬂakes is presented inFig. 6.

The main component of desquamated skin cells is the protein keratin (Voloshina et al., 2017). The adsorption spectra for keratin and skin are characterized by the two protein bands: amide I and amide II which are peaking around 1650 and 1550 cm⁻¹, respectively (Cestelli et al., 2012; Yu et al., 2012). The spectral region 2800–3000 cm⁻¹ en- compasses the C-H stretching of CH2and CH3in lipid chains (Yu et al., 2012; Liou et al., 2009). The spectral signatures for these compounds in house dust corresponded well with those of the human skin ﬂakes (Fig. 6). It has previously been shown that human epithelial keratin is an abundant protein in airborne dust (Voloshina et al., 2017; Fox et al., 2008). Since the house dust sample is such a heterogeneous mix of organic matter, there is a possibility that these protein and lipidﬁn- gerprints also are derived from other sources (such as plant cells and microorganisms).

5. Conclusions

This study describes an easy and eﬃcient method for extraction a respirable fraction of house dust from vacuum cleaner bags. The respirable fraction of house dust is of great interest since the airways as a route of exposure to house dust is not yet fully understood. House dust is an important environmental matrix to monitor and this extraction method might be valuable for risk assessment following an inhalation exposure to house dust.

5.1. Limitations of the study

A limitation with this study is that there were no instruction about the vacuum cleaning to the people in the residential. This leads to missing information regarding time of dust collection, brand- of vacuum cleaner and vacuum cleaner bags. In this study only one replicate was used for the physical and chemical determinations (except for determination of dry matter- and ignition residue, where three replicates were used). Even though there was an extensive homogenization of the sample, it cannot be excluded that if more replicates had been analyzed there would have been variations between the results of each analysis.

Acknowledgements

The authors acknowledge Fernando Acevedo and the Acevedo Biochem Consulting for development of the equipment to sieve and process the dust. The facilities and technical assistance of the Umeå Core Facility for Electron Microscopy (UCEM) at the Chemical Biological Centre (KBC), Umeå University. Maria Malmlöf, Mikael Mikko, Mattias Nowenwik and Ewa Selg at Inhalation Sciences for scientific advice and SEM imaging following aerosolization with the PreciseInhale system. Zoltan Bacsik and Lars Eriksson at the Stockholm University for the specific surface area determination and XRD analyzes respectively. Andrey Shchukarev at Umeå University for the XRF analysis. Åke Bergman for scientific discussions and Bo Watz for practical advice at Swetox. The Swedish Research Council Formas. Dnr 216–2013-1966.

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Fig. 6. FTIR spectra of house dust (black) and desquamated skin cells (grey). The arrow marks the spectral regions for bands correlated to protein and lipid content.

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