ARTICLE IN PRESS Environmental Pollution xxx (2010) 1–7 Contents lists available at ScienceDirect Environmental Pollution journal homepage: www.elsevier.com/locate/envpol Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses R. Mitchell a,*, B.A. Maher a, R. Kinnersley b a Centre for Environmental Magnetism and Palaeomagnetism, Lancaster Environment Centre, University of Lancaster, Lancaster LA1 4YQ, UK b Evidence Directorate, Environment Agency, Olton Court, 10 Warwick Road, Olton, Solihull B92 7HX, UK This research uses biomagnetic techniques to enable quantitative mapping of particulate pollution distribution at uniquely high spatial resolution. article info abstract Article history: Evaluation of health impacts arising from inhalation of pollutant particles <10 mm (PM10) is an active Received 1 September 2009 research area. However, lack of exposure data at high spatial resolution impedes identification of Received in revised form causal associations between exposure and illness. Biomagnetic monitoring of PM10 deposited on tree 11 December 2009 leaves may provide a means of obtaining exposure data at high spatial resolution. To calculate ambient Accepted 16 December 2009 PM10 concentrations from leaf magnetic values, the relationship between the magnetic signal and total PM10 mass must be quantified, and the exposure time (via magnetic deposition velocity (MVd) Keywords: calculations) known. Birches display higher MV (w5cmÀ1) than lime trees (w2cmÀ1). Leaf saturation Magnetic biomonitoring d w Deposition velocity remanence values reached ‘equilibrium’ with ambient PM10 concentrations after 6 ‘dry’ days (<3 mm/day rainfall). Other co-located species displayed within-species consistency in MV ; robust PM10 monitoring d Tree leaves inter-calibration can thus be achieved, enabling magnetic PM10 biomonitoring at unprecedented spatial Inter-species calibration resolution. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction An additional problem with data from conventional monitoring stations is the height of their air inlets, often situated in excess of A growing body of literature (e.g. Curtis et al., 2006; Lipmann, 3 m. Traffic-derived PM10 values decrease not only with increased 2007; Schwarze et al., 2006; Zeger et al., 2008) documents the distance from roads, but also with increased height (e.g. Maher adverse health effects of exposure to fine-grained pollutant parti- et al., 2008; Mitchell and Maher, 2009). Thus, PM10 data from the cles, i.e. those with aerodynamic diameters below 10 mm in diam- conventional pollution monitoring networks may be a weak indi- eter (PM10), and particularly those below 2.5 mm (PM2.5). However, cator of individual human exposure. the pollution exposure data relied upon by many epidemiological A number of studies have used the magnetic properties of studies are often sourced from low spatial-resolution networks of deposited particles as a proxy for particulate pollution levels monitoring stations, which are unlikely to capture possibly fine (e.g.Hanesch et al., 2007; Maher et al., 2008; Matzka and Maher, scale variations in PM concentration and/or particle size across the 1999; Szo¨nyi et al., 2008). Magnetic techniques, using natural diverse urban environment. For example, in large population surfaces as passive collectors of particulate pollution, are sensitive, studies (e.g. Dominici et al., 2006; Karr et al., 2006; Woodruff et al., rapid, and relatively cheap; and passive collectors require no power 2006; Zeger et al., 2008), PM10 exposure has frequently been source or protection from vandalism. Strong correlation has been characterised as the average PM10 value at the ‘nearest’ monitoring demonstrated between leaf saturation remanent magnetisation station (i.e. within 5 miles of residence). Such coarse-scale data (SIRM) and/or magnetic susceptibility values and the presence of reduce the potential for identifying and quantifying specific causal pollution particles, produced by combustion and/or abrasion links between the degree of exposure to PM10 and the likelihood of processes (e.g. Gautam et al., 2004; Halsall et al., 2008; Maher et al., adverse health impacts within a population. 2008), and toxic metals, such as lead and iron (e.g. Maher et al., 2008). Strong correlation between roadside leaf SIRMs and ambient PM10 concentrations (from co-located pumped-air samples) * Corresponding author. Tel.: þ44(1524) 510221; fax: þ44 (1526) 510269. suggests that magnetic biomonitoring, using tree leaves as passive E-mail address: [email protected] (R. Mitchell). pollution collectors, can be a robust technique for quantifying 0269-7491/$ – see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.envpol.2009.12.029 Please cite this article in press as: Mitchell, R., et al., Rates of particulate pollution deposition onto leaf surfaces: Temporal and inter-species magnetic analyses, Environ. Pollut. (2010), doi:10.1016/j.envpol.2009.12.029 ARTICLE IN PRESS 2 R. Mitchell et al. / Environmental Pollution xxx (2010) 1–7 À7 ambient concentrations of PM10 levels at unprecedentedly high co-located Hi-Vol air sampler, fitted with magnetically clean (SIRM ¼ 1 Â10 Amps spatial resolution and at pedestrian-relevant heights (Mitchell and (A)) PTFE filters (1 mm pore size). The conventional method for calculating deposi- tion velocities (V ) is to divide the particle flux to the sampling surface over a known Maher, 2009). So far, however, the rate and temporal variability of d period of time (mass/m2/s) by the ambient concentration (mass/m3). Magnetic magnetic particle deposition on tree leaves, and on different deposition velocities were calculated following the conventional approach, but species of trees, have yet to be examined. substituting SIRM for mass; Deposition to vegetation surfaces is also significant in its own right. It is a sink for atmospheric particles, and a route by which MVd ¼ F=C (1) pollutants and particulate nutrients (such as ammonium nitrate) 2 3 can enter the biosphere. Dry deposition of pollution particles (Pryor where F ¼ SIRMleaf/m s and C¼ SIRMfilter/m , A second sampling campaign was carried out between 10/05/08–03/06/08 at the et al., 2007) is considered more important than wet deposition, main access road to Lancaster University (site 2), a site with enhanced traffic-derived particularly near to pollution sources (e.g. Businger, 1986; Pryor particulate pollution levels. Again, prior to exposure, ‘clean’ leaf samples were taken et al., 2007). Some data exist for particulate dry deposition rates to from six trees of each species; these trees were then placed at the roadside. Half of foliage both under controlled, laboratory and wind-tunnel condi- the trees were planted close to the road, on the uphill side of the roundabout tions (e.g. Caffrey et al., 1998; Dai et al., 2001; Parker and Kin- approach to maximise exposure to vehicle-sourced pollution (Matzka and Maher, 1999; Mitchell and Maher, 2009). Samples were collected 48-hourly from w0.3 m nersley, 2004), and field conditions (e.g. Petroff et al., 2008; Pryor height. The remaining trees were not planted but placed at the roadside only during et al., 2008). However, the range of published deposition values is the morning and evening peak traffic flow periods (08:15–10:15, 15:30–17:30). At all large, reflecting both the differing methods of measurement and other times, they were stored in the glasshouse. Leaf samples were collected concurrently with the planted trees (i.e. after 4 Â 2 h exposures) from w0.3 m the complex dependence of deposition velocities (Vd) on variables height. Pumped-air samples (240 L) were collected, at a rate of 2 l/min, from co- such as particle size and density, terrain, vegetation, meteorological located SKC Leland Legacy personal monitors with magnetically clean conditions, and chemical species (e.g. Zhang et al., 2001). À7 (SIRM ¼ 1 Â10 A) PTFE filters (1 mm pore size) in IoM-type PM10-selective sampler Measurements under natural conditions are particularly difficult to heads, during each peak traffic flow period. After exposure, all filters were imme- obtain (Kinnersley et al.,1994). Artificial sample collectors currently diately weighed then placed in magnetically clean (SIRM ¼ 0.05 Â 10À6 A/m) 10 cc available are unable to reproduce accurately the effects of real plastic pots and taken to the laboratory for magnetic analysis. Correlations were calculated between leaf magnetic values and the indepen- receptor surface morphology, canopy structure and texture (Wesely dently measured ambient PM10 concentrations. In order to identify the time period and Hicks, 2000), and therefore may provide unrealistic deposition required for particulate accumulations on leaves to attain dynamic equilibrium with estimates. ambient concentrations, stepwise exclusion correlation calculations were used. Here, we report a magnetic biomonitoring study which has Initially, all samples were included in the correlation calculation. Samples were then removed one at a time, in time-series order, and the correlation (R2) and significance measured deposition velocities to natural surfaces under field re-calculated. The optimum solution is the one in which the correlation and the conditions. We examined glasshouse-grown ‘clean’ leaves and co- sample number included in the calculation are maximised. located pumped-air samples at a rural ‘background’ site, in order to To examine the variability of leaf SIRMS between different tree species, leaves assess the rate of PM10