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Modeling, Measuring, and Characterizing Airborne Particles: Case Studies From Southwestern Luxembourg a
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Saskia Buchholz , Andreas Krein , Juergen Junk , Arno C. Gutleb a
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, Laurent Pfister & Lucien Hoffmann
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Centre de Recherche Public–Gabriel Lippmann, Department of Environment and Agro-biotechnologies, Belvaux, Luxembourg Available online: 26 Jul 2011
To cite this article: Saskia Buchholz, Andreas Krein, Juergen Junk, Arno C. Gutleb, Laurent Pfister & Lucien Hoffmann (2011): Modeling, Measuring, and Characterizing Airborne Particles: Case Studies From Southwestern Luxembourg, Critical Reviews in Environmental Science and Technology, 41:23, 2077-2096 To link to this article: http://dx.doi.org/10.1080/10643389.2010.495930
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Critical Reviews in Environmental Science and Technology, 41:2077–2096, 2011 Copyright © Taylor & Francis Group, LLC ISSN: 1064-3389 print / 1547-6537 online DOI: 10.1080/10643389.2010.495930
Modeling, Measuring, and Characterizing Airborne Particles: Case Studies From Southwestern Luxembourg SASKIA BUCHHOLZ, ANDREAS KREIN, JUERGEN JUNK, ARNO C. GUTLEB, LAURENT PFISTER, and LUCIEN HOFFMANN Centre de Recherche Public–Gabriel Lippmann, Department of Environment and Agro-biotechnologies, Belvaux, Luxembourg
The World Health Organization and the European Union highlight human exposure to air pollution, especially particulate matter as a priority environmental problem. Nevertheless, there are several problems related to the modeling of particulate matter in space and time as well as the chemical characterization of the involved particles. Previously used models are not applicable in all situations or particulate matter concentrations are often not detailed enough in respect to time resolution. Usually applied chemical methods to describe particulate matter composition are destructive and no information on surface composition can be obtained. Therefore, the authors’ main objective was the assessment of indoor and outdoor particle concentrations in southwestern Luxembourg applying state-of-the-art modeling approaches and measuring actual particulate matter concentrations with a high temporal resolution under various exposure scenarios. The spatial distribution of PM10 was modeled. Additional indoor particle measurements were carried out in a passenger car compartment and in an office building. Furthermore, chemical properties, assessed with a secondary ion mass spectrometer, show a complex mixture of elements on the surface of selected particles with distinct hot spots of potentially dangerous heavy metals. KEY WORDS: health impact, heavy metals, indoor air pollution, NanoSIMS 50, PM10, PM2.5, SelmaGIS Address correspondence to Saskia Buchholz, Centre de Recherche Public–Gabriel Lippmann, Department of Environment and Agro-biotechnologies, 41 rue du Brill, Belvaux, L-4422, Luxembourg. E-mail:
[email protected] or
[email protected] 2077
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1.
INTRODUCTION
Human exposure to high ambient air pollutant concentrations is one of the urgent environmental problems in Europe.1 Various studies suggest that both long- and short-term exposure to air pollution damage human health, leading to greater morbidity and shorter life expectancy.2–4 Because of their adverse effects on human health and on the environment, the World Health Organization (WHO), as well as the European Commission, highlight particulate matter (PM) as a priority air pollutant.3 Many epidemiological studies have shown that particularly short-term episodic exposure to aerosol particles increases the risk for hospital admission, cardiovascular and respiratory diseases, and mortality,5–7 especially in elderly people, children, and persons with medical history. During the last decade it has been widely recognized that particulate matter with aerodynamic diameters 3.5 t) cause—with 3% of the total traffic—nearly 50% of PM10 traffic emissions. The industry compared to the traffic has a minor effect on the PM10 concentration levels.
4.2 Indoor Air Pollution The measurements of passenger car indoor air pollution were conducted during stable high-pressure weather conditions, with the last precipitation event
FIGURE 2. Annual mean PM10 concentrations for 2004. (Color figure available online).
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FIGURE 3. Annual mean PM10 concentrations for 2004 caused by on-road transport. Measurement route = →. (Color figure available online).
having occurred four days prior. The background level of PM10 in ambient air at the nearby official air quality station (rural background) showed mean hourly concentration values of ∼20 µg/m3. The driving route of the vehicle, in which the measurements have been realized, was based on the modeling result and indicated by the arrows in Figure 3. The objective of this case study was to investigate the influence of the higher outdoor fine dust concentrations caused by the traffic on the passenger compartment concentrations. Starting point was the roundabout (I) in the northwestern part of the map following the arrows through the city of Esch-sur-Alzette. High concentrations occurred at the railway station and the bus terminal (II), followed by the motorway (III) on the way back to the roundabout.48 Concentrations of PM10 and PM2.5 were measured under two different conditions during the measurement trips inside the car (Figures 4 and 5). At the beginning of trip I the PM10 concentrations rise because of the turbulences induced by two passengers getting into the vehicle (Figure 4). In addition, unfiltered ambient air enters the car through the open doors. Furthermore, sedimented particles in the air conditioning ventilation are resuspended (see scatter plot in Figure 4). The indoor pollutant concentrations are influenced by the increasing traffic intensity entering the City of Esch-surAlzette (11:45–11:48 MEZ). In the area nearby the bus terminal, the highest indoor concentrations could be observed (II). At this location especially, the waiting busses and taxis with running engines and traffic jams caused these high concentrations. Because the measured dust concentrations mainly
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FIGURE 4. PM10 and PM2.5 passenger compartment concentrations (closed windows, running air conditioning). The numbers refer to Figure 3.
consist of PM2.5, we conclude that the filters of the air conditioning system mostly retain PM10 particles. After passing by the bus terminal and leaving the city center again (11:49 MEZ) the pollutant concentrations are decreasing again rapidly. Many studies indicate cigarette smoke as an important source of particulate matter and indoor air pollution.49–52 For this reason, another measurement trip along the same route investigated (a) the influence of cigarette smoke on the particulate matter concentration in a car and (b) the duration
FIGURE 5. PM10 and PM2.5 passenger compartment concentrations (closed windows, running air conditioning, one cigarette smoked).
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until the high dust concentrations are reduced to a normal level by the air conditioning system. During the trip, a cigarette was smoked in the front of the passenger compartment. All car windows remained closed. The time series of the measured concentrations are shown in Figure 5 (please note logarithmic scale in this figure). Directly after lightening the cigarette (11:10 MEZ) the concentrations increased sharply up to 640 µg/m3 for PM10 and 632 µg/m3 for PM2.5, respectively. At this time the traffic-induced outdoor pollution showed only minor effects on the measurements of the total concentration. After smoking the single cigarette (11:19 MEZ), it took between 6 and 7 min (depending on the chosen air conditioning level) until the concentration reached the initial level. The additional scatter plot in Figure 5 shows that the main proportion of the fine dust consists of particles with an aerodynamic diameter of 2.5 µm or less. Our results show that there is a significant exchange between indoor and outdoor polluted air via the air conditioning system. A fully functional and well-maintained filter system of the air conditioning is able to significantly reduce the PM10 fraction of the fine dust. An accumulation of particles during the trip could not be observed. The circulation induced by the air conditioning is not strong enough to keep all particles in suspension. According to Klepeis et al.,17 the majority of the people spend most of their time indoors (private and working time). Therefore, besides the investigation of pollutants inside cars the investigation of exposition of people inside buildings is of great interest. Indoor fine dust concentrations are affected by ambient concentrations, air exchange rates, penetration factors, and deposition and resuspension mechanisms.53 Therefore, further measurements were conducted on the base floor of a two-floor office building (about 200 working places) in the area of investigation. Smoking was prohibited and the building was not equipped with an air conditioning system. The nearest major road was about 250 m away from the building, and no construction work was observed. The measurements were conducted in accordance with the ISO 16000 standard.54 The GRIMM spectrometer was placed in 3 m distance to an entry door, 0.5 m away from the next wall, and particles were collected at a height of 1.3 m. In the weekly measurement period from Sunday, August 6, until Saturday, August 12, 2007, clear daily cycles during the working days were shown (Figure 6). As Saturdays and Sundays are weekend days and the building was closed, there were constant low fine dust concentrations. Parallel to the particulate matter measurements, air temperature was recorded (blue line in Figure 6). This gave us an indication of the opening of the entry door. Cool air flushed into the building, leading to higher PM concentrations due to turbulences, resuspension of sedimented particles, and an inflow of polluted air. Further peaks could be related to people passing by the spectrometer, or
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FIGURE 6. Air temperature and PM10 and PM2.5 concentrations measured in an office building in Esch-sur-Alzette, period of August 6–12, 2007. (Color figure available online).
smoking cigarettes outside in front of the door. After 8 pm, the dust concentrations decreased significantly when the building was locked and no further indoor activities took place. In less than 1 hr, most of the dust particles sedimented. Overall, the measured PM10 and PM2.5 concentrations were rather low. Table 3 illustrates that during the weekend the low concentrations of dust mainly consisted of PM2.5 which sediments slower than PM10. Our results of PM2.5 concentrations agree well with other studies.53,55,56 According to the relevance of particles to human health, not only are the absolute concentrations important, but the chemical properties of the single particles are as well. Therefore, selected particles from the area of investigation, collected on filters, were analyzed with NanoSIMS 50.
4.3 Chemical Characterization of Fine Dust With NanoSIMS 50 The physicochemical and biological properties of particulate matter are relevant for possible interactions with the human organism.1 Generally, the chemical composition seems to be of similar importance than particle size and in addition the chemical composition can modify associations between TABLE 3. Daily work time averages (6 am till 8 pm) of PM10 and PM2.5 concentrations [µg/m3], calculated from 5 minutes mean values Date Weekday PM10 PM2.5
6.8.2007 Sunday 5.8 5.7
7.8.2007
8.8.2007
9.8.2007
10.8.2007
Monday 16.8 8.9
Tuesday Wednesday Thursday 18.6 18.6 19.0 7.8 9.1 8.8
11.8.2007
12.8.2007
Friday 13.9 6.8
Saturday 2.1 2.1
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FIGURE 7. Different chemical compounds at the surface of two dust particles characterized with NanoSIMS 50. (Color figure available online).
PM2.5, morbidity, mortality, and existing medication.14,57,58 The place of sedimentation of particles inside the human respiratory tract is determined by their aerodynamic characteristics. Particles can act as a carrier for different pollutants, leading to inflammations or even worse.59 They can be accumulated depending on their size directly in the tissue or be transported into the bloodstream. Fine dust was sampled with DERENDA low-volume samplers (sampling time 24 hr) in a height of 1.3 m near the office building and stored on Teflon filters with a pore size of 2 µm, scratched from the filter surface and placed on the sampling carrier. Secondary ions of the cluster 12C14N−, 32S−, 35Cl−, 63 Cu−, 75As−, and 118Sn− were collected in the electron multipliers of the NanoSIMS 50. The concentrations highlighted in Figure 7 are semiquantitative and increase from black to red coloring. Two different particles are shown consisting at the surface of various materials. An unstructured matrix containing the 12C14N− cluster forms the surface of the main body of the particle (Figure 7, left). The heavy metal copper is concentrated in hot spots at the surface of the particle. Different hot spots are also highlighted by the presence of chlorine. Some other elements such as tin show only minor concentrations. On the other particle (Figure 7, right) potentially toxic arsenic is irregularly distributed on the surface with higher concentrations at the bottom of the particle. The toxicity is based on the speciation of arsenic, which cannot be detected by NanoSIMS 50. Again, copper and sulfur are concentrated on several hot spots, and the element tin is also not found.
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The surface characteristics can additionally be used to identify material sources. Copper and sulfur potentially refer to burning or melting processes from the local steel industry. With the goal to identify different sources of atmospheric dust, several hundreds of single particles have to be analyzed with this technique, limiting this method because of the time consuming and cost intensive approach.
5. CONCLUSIONS The evidence on adverse effects of particulate air pollution on public health has led to ambitious standards for concentrations of particulate matter in ambient air. A new threshold for particles smaller than 2.5 µm was created because particles of that size have a much greater probability of reaching the small airways and the alveoli of the lung than do coarser particles. Fine particulates with an aerodynamic diameter of less than 2.5 µm have an atmospheric lifetime in the order of days. The adsorption of heavy metals or polycyclic aromatic hydrocarbons onto surfaces of near surface atmospheric dust is a fundamental pathway for the distribution of these toxic compounds in the environment. The chemical assessment is as important as the mass concentration of dust in the ambient air. Furthermore, even a chemical analysis tells nothing about the surface structure of particles and a possible impact on human health. So far, the heterogeneities on the surface of particles could only be studied by transmission electron microscopy. Recently, SIMS was extended to the nanometer scale, which makes this technique interesting in characterizing the individual particles.60 Our NanoSIMS analyses highlight that the particle surfaces show different chemical properties that play an important role on health effects but are not covered by the EU legislation. Furthermore, indoor pollution is also not targeted by any regulation. The assessment of the exposure of inhabitants to high particulate concentrations is very complex. Results of relevant studies highly depend on the selection of models, measurement techniques, and the selection of the measurement points. Hot spots of air pollution can be identified by different model approaches, but these techniques are not capable of replacing direct measurements. In general, only precise measurements of high temporal and spatial resolution provide the necessary information to assess the complex interrelationship between atmospheric conditions and particle concentrations in the lower atmosphere. The majority of the air pollution models concentrate on the outdoor air pollution; models for indoor concentrations are scarce.61 Because of the fact, that the majority of the people living in developed countries spent most of their time indoors, these models will gradually become more important in the future. To develop and improve such models, intensive measurement campaigns of indoor air pollution have to be carried out.
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Considering the health aspect in such models, information about mass concentration, numbers of particles, and about the chemical properties at the particle surface is required.
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ACKNOWLEDGMENTS The authors gratefully acknowledge the financial support of the Minist`ere de la Culture, de l’Enseignement sup´erieur et de la Recherche in the PhD scholarship for Saskia Buchholz entitled “Assessment of Air Pollution Via State-of-the-Art Field Observations and Multi-Scale Numerical Modeling for Luxembourg With a Focus on the Capital City.” The authors acknowledge the assistance of Franc¸ois Barnich and Jean-Franc¸ois Iffly with laboratory and field work. Jean-Nicolas Audinot conducted the SIMS measurements, many thanks to him. The authors thank the National Research Fund of the Grand Duchy of Luxembourg for the funding the NanoSIMS 50 part of this study in the frame of the project “Analyse d’´echantillons environnementaux a` l’´echelle du nanom`etre.” This review is the extended version of a lecture given on the conference: Health Aspects of Indoor and Outdoor Air Pollution, Luxembourg, November 12, 2008, that was funded by the FNR Luxembourg.
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