Particulate matter sources on an hourly timescale in a rural community during the winter

Abstract

Particulate matter (PM) sources at four different monitoring sites in Alexandra, New Zealand, were investigated on an hourly timescale. Three of the sites were located on a horizontal transect, upwind, central, and downwind of the general katabatic flow pathway. The fourth monitoring site was located at the central site, but at a height of 26 m, using a knuckleboom, when wind conditions permitted. Average hourly PM₁₀ (PM with an aerodynamic diameter <10 μm) concentrations in Alexandra showed slightly different diurnal profiles depending on the sampling site location. Each location did, however, feature a large evening peak and smaller morning peak in PM₁₀ concentrations. The central site in Alexandra experienced the highest PM₁₀ concentrations as a result of PM transport along a number of katabatic flow pathways. A significant difference in PM₁₀ concentrations between the central and elevated sites indicated that a shallow inversion layer formed below the elevated site, limiting the vertical dispersion of pollutants. Four PM₁₀ sources were identified at each of the sites: biomass combustion, vehicles, crustal matter, and marine aerosol. Biomass combustion was identified as the most significant source of PM₁₀, contributing up to 91% of the measured PM₁₀. Plots of the average hourly source contributions to each site revealed that biomass combustion was responsible for both the evening and morning peaks in PM₁₀ concentrations observed at each of the sites, suggesting that Alexandra residents were relighting their fires when they rose in the morning. The identification of PM sources on an hourly timescale can have significant implications for air quality management.

Implications: 

Monitoring the sources of PM₁₀ on an hourly timescale at multiple sites within an airshed provides extremely useful information for air quality management. Sources responsible for observed peaks in measured diurnal PM₁₀ concentration profiles can be easily identified and targeted for reduction. Also, hourly PM₁₀ sampling can provide crucial information on the role meteorology plays in the development of elevated PM₁₀ concentrations.

Introduction

Particulate matter (PM) is well known to have adverse effects on human health and a range of environmental effects, including local reductions in visibility and effects on the earth’s radiative balance (Dockery et al., 1993; Nel, 2005; Pósfai and Buseck, 2010; Russell and Brunekreef, 2009; Tsai and Cheng, 1999). Therefore, the benefits of understanding the sources and factors contributing to elevated PM concentrations are direct and tangible. In New Zealand, PM concentrations have been shown to have distinct diurnal cycles, with peak concentrations occurring during the evening and morning (Trompetter et al., 2010). Currently, very little is known about the sources and factors responsible for the observed diurnal cycles, although domestic wood combustion for home heating is known to be a significant contributor to PM₁₀ concentrations in New Zealand during the winter (Ancelet et al., 2012b, 2013; Davy et al., 2012).

We have recently reported the first PM source apportionment study using hourly data obtained from two sampling sites in the rural community of Masterton, New Zealand (Ancelet et al., 2012a). In that study, biomass combustion was identified to be the dominant PM source during both the evening and the morning. To identify whether this situation was unique to Masterton, an intensive high-temporal-resolution monitoring campaign was undertaken in Alexandra, New Zealand (latitude −45.16°, longitude 169.22°) during the 2011 winter. Alexandra is a rural town located in an inland basin with a population of approximately 4800. Despite its small population, Alexandra suffers from poor air quality during the winter when domestic combustion for home heating and strong temperature inversions that limit the dispersion of pollutants are common.

In this study, positive matrix factorization (PMF) was used to identify the major PM₁₀ (PM <10 μm in aerodynamic diameter) sources at four sites in Alexandra on an hourly timescale. PMF is a multivariate method capable of resolving factors contributing to PM samples. PMF results are directly interpretable as mass contributions from each factor (source) (Paatero, 1997; Paatero and Tapper, 1994; Song et al., 2001). Two receptor models are available to perform PMF, PMF2 (Paatero, 1997) and U.S. Environmental Protection Agency (EPA) PMF (EPA, 2008). Despite some differences in model operation (Paatero, 1999), PMF2 and EPA PMF have been shown to provide similar results with some minor differences in the final solutions (Kim and Hopke, 2007).

Using hourly source contributions and meteorological data from each of the sites, potential PM transport mechanisms were also identified. High-temporal-resolution source apportionment studies can provide unique and highly relevant information for the implementation of PM mitigation strategies and have experienced more attention recently (Moreno et al., 2013a, 2013b; Pancras et al., 2013).

Experimental

Sample collection

Ambient air monitoring was conducted at four locations in Alexandra. Three of the sites were located along the general katabatic flow pathway (upwind, central, and downwind). The fourth site (Aloft) was also located centrally, but was raised to a height of 26 m above ground level using a knuckleboom when wind conditions permitted (<3 m sec⁻¹). Under higher wind speeds, the knuckleboom was kept at ground level. This type of experimental setup has never been reported before and Figure S1 in Supplemental Materials presents a schematic illustration of the sampling site locations. The sampling site locations were designed to provide an indication of PM transport horizontally and vertically within the Alexandra airshed.

The upwind site was located on the grounds of the Alexandra Bowling Club (ABC) (latitude −45.143957°, longitude 169.225102°, 137 m elevation). The ABC site was situated approximately 600 m northwest of the central site and 70 m from the nearest road. The central and elevated sites were located at the Alexandra Girl Guides center (GG) (latitude −45.145753°, latitude 169.230385°, 137 m elevation) and were approximately 50 m from the nearest road. The GG site was co-located with an ambient air quality monitoring station used for compliance monitoring by the Otago Regional Council. The downwind site was located in an open area next to the offices of the Central Otago District Council (CODC) (latitude −45.152455°, longitude 169.232152°, 139 m elevation). The CODC site was approximately 1 km southeast of the GG site and 100 m from the Clutha River. Road works were being undertaken infrequently approximately 500 m from the CODC site. The land around each of the sites was flat and surrounded by open space or buildings no more than two stories high. Figure S2 presents the locations of each of the sampling sites.

Each site was equipped with a Streaker sampler (PIXE International Corporation, Tallahassee, FL, USA), an E-BAM (Met One Instruments, Inc., Rowlett, TX, USA), and a meteorological station at a height of 10 m (Vaisala WXT520) in the same fashion as previously reported (Ancelet et al., 2012a). In this study, a total of 47 samples, or 47 hr, were collected on each set of size-resolved (PM_10–2.5 and PM_2.5) filters. The monitoring program ran from April to June 2011 and a total of 7406 samples were collected among the four sites (1784 from ABC, 2054 from GG, 1880 from CODC, and 1690 [522 when raised to 26 m] from the Aloft site).

Elemental analysis

Ion beam analysis (IBA) was used to measure the concentrations of elements with atomic numbers above neon in the PM collected. IBA measurements were carried out at the New Zealand Ion Beam Analysis Facility operated by the Institute of Geological and Nuclear Sciences (GNS) in Gracefield, Lower Hutt, New Zealand (Trompetter et al., 2005). Further details on the IBA techniques used, analytical uncertainties, and limits of detection have been reported previously (Ancelet et al., 2012a). Black carbon was measured using a M43D digital smoke stain reflectometer (Ancelet et al., 2011). Prior to the PMF analyses, data and uncertainty matrices were prepared for each site in the same manner as in previous studies (Polissar et al., 1998; Song et al., 2001).

Receptor modeling

Receptor modeling and apportionment of PM mass by PMF was performed using the EPAPMF version 3.0.2.2 program in accordance with the user’s guide (EPA, 2008). With PMF, sources are constrained to have non-negative species concentrations; no sample can have a negative source contribution and error estimates for each observed point are used as point-by-point weights. This is a distinct advantage of PMF, since it can accommodate missing or below-detection-limit data that are a common feature of environmental monitoring (Song et al., 2001). Data screening and the source apportionment were performed in the same manner as previously reported (Ancelet et al., 2012a). Table S1 provides a summary of the parameters used for the PMF analyses and the diagnostics obtained for each of the sites.

Results and Discussion

PM₁₀ concentrations

PM₁₀ concentrations at all four of the sites displayed distinct diurnal cycles. Figure 1a presents the average hourly PM₁₀ concentrations at the ABC, GG, and CODC sites over the entire sampling period. From Figure 1a it is apparent that absolute PM₁₀ concentrations in Alexandra are strongly dependent on the sampling location. Although each of the sites had peak PM₁₀ concentrations during the evening, the GG site generally experienced higher PM₁₀ concentrations than the ABC and CODC sites and peak PM₁₀ concentrations at the GG site (7 p.m. to midnight) occurred earlier than at the other sites (9 p.m.–2 a.m.). This is probably because the GG site was located in a more densely populated area than the ABC and CODC sites, which were near the outskirts of Alexandra and had fewer immediate PM sources. A morning peak in PM₁₀ concentrations (8–10 a.m.) was also apparent at each of the sites, but was much more pronounced at GG. Compared with the CODC site, PM₁₀ concentrations at the ABC site peaked earlier and remained elevated for longer. It is likely that the proximity of the CODC site to the Clutha River (within 100 m) contributed to the lower PM₁₀ concentrations measured because of cold air drainage along the river.

Figure 1. Average hourly PM₁₀ concentrations at (a) the Bowling Club, Girl Guides, and Central Otago District Council office sites and (b) at the Girl Guides and Aloft sites during periods when the knuckleboom was raised.

Figure 1b presents average hourly PM₁₀ concentrations at the GG and Aloft sites during periods when the knuckleboom was raised (261 hr total). Since the knuckleboom was only raised when wind speeds were low (during anticyclonic atmospheric conditions), PM₁₀ concentrations measured at the GG site were higher than during periods when the knuckleboom was not raised because of the formation of strong temperature inversions that limited the transport of PM. Average hourly PM₁₀ concentrations at the GG site during periods when the knuckleboom was raised showed a trimodal diurnal pattern, with peak PM₁₀ concentrations occurring at 7 p.m., from 10 to 11 p.m., and at 8 a.m. In contrast to the ground-level site, average hourly PM₁₀ concentrations at the Aloft site (26 m height) had a bimodal diurnal pattern, with a broad evening peak (6 p.m.–2 a.m.) and a morning peak at 9 a.m. It is also evident from Figure 1b that average hourly PM₁₀ concentrations at the ground-level GG site were significantly higher than those aloft from 6 p.m. to midnight and from 8 to 10 a.m., suggesting the formation of a stable inversion layer below the height of the Aloft site. Further supporting this conclusion, average wind speeds and temperatures were higher at the Aloft site than those at GG between 7–11 p.m. and 8–9 a.m. A study on vertical BC profiles in Alexandra has also shown that a shallow inversion layer formed lower than 26 m (Trompetter et al., 2013). Between 1 and 7 a.m., average hourly PM₁₀ concentrations at the Aloft site were slightly higher than at the GG site, indicating that shallow drainage winds were likely responsible for the large decrease in PM₁₀ concentrations measured during the early morning. It is also likely that during these hours the height of the inversion layer increased, increasing the vertical mixing of pollutants (Pournazeri et al., 2012).

Comparisons of daily average PM₁₀ concentrations among the four sites revealed that ABC and CODC did not exceed the New Zealand National Environmental Standard for PM₁₀ of 50 μg m⁻³ (24-hr average) on any day during the study period, whereas the Aloft and GG sites had 1 and 12 exceedances, respectively, during this study. It is important to note that E-BAMs are not certified for air quality compliance monitoring, but it is clear that the sampling location can have a significant impact on measured PM₁₀ concentrations in Alexandra.

The local meteorology in Alexandra was investigated on an hourly basis to gain a better understanding of PM transport. Figure S3 presents a wind rose plot over the entire sampling period from GG. Wind rose plots for ABC, CODC, and Aloft were similar to that from GG.

A number of features are apparent from Figure S3. First, winds during the sampling period were predominantly from the southwest and north, with westerly and southerly components also strongly contributing. Northerly winds were characterized by low wind speeds (<2 m sec⁻¹). Using the high-temporal-resolution data available in this study, hourly pollution roses for each of the sites were developed using the R statistical and Openair packages (Carslaw 2012; Carslaw and Ropkins, 2012; R Development Core Team, 2011). Figure S4 presents hourly PM₁₀ pollution roses for the GG site. Figure S4 suggests that the elevated PM₁₀ concentrations measured at GG were the result of katabatic flows, generally from the north. Interestingly, the pollution roses also suggest that katabatic flows from other directions also influence the GG site. Since Alexandra is located in a basin, it seems likely that PM emitted during the evening could be transported through a number of different katabatic flow pathways.

In contrast to the GG site, hourly pollution roses for CODC (Figure S5) indicated that, during the morning and evening, PM₁₀ was transported from the north by katabatic flows. This result demonstrates that, despite their close proximity, different areas within an airshed can be impacted by PM in different manners.

Sources of ambient PM₁₀

Tables S2–S5 present the average, maximum, and median hourly concentrations of species used for source apportionment at the ABC, GG, CODC, and Aloft sites, along with standard deviations, average uncertainties, average limits of detection, and the number of samples above the limit of detection for each species.

Reconstructed masses (RCMs) determined using the elemental data accounted for 26%, 23%, 27%, and 21% of the PM₁₀ mass at the ABC, GG, Aloft, and CODC sites, respectively (Malm et al., 1994). Because numerous species, including organic carbon, were not quantified, the relatively low RCMs are not surprising. The application of PMF to hourly elemental data from each of the sites revealed four PM₁₀ sources at each of the sites. The source profiles obtained for GG are presented in Figure 2, whereas the source profiles for ABC, CODC, and Aloft are presented as Figures S6, S7, and S8, respectively. The error bars shown in Figures 2 and S6–S8 indicate standard deviations determined from bootstrapping in the EPAPMF program. Limitations in the bootstrapping technique have previously been discussed (Ancelet et al., 2012a).

Figure 2. Source profiles obtained at the Alexandra Girl Guides site.

The sources presented in Figures 2, S6, S7, and S8 were found to explain 96%, 95%, 98%, and 99% of the PM₁₀ mass measured by the E-BAMs at ABC, GG, Aloft, and CODC, respectively, after regression using PM₁₀ concentrations. Factor 1 contributed to 86%, 90%, 91%, and 88% of the PM₁₀ mass at ABC, GG, Aloft, and CODC, respectively. It was identified as a biomass combustion source because of high black carbon (BC) and fine K loadings. Potassium is usually used alongside BC as a marker for biomass burning, and wood combustion in particular (Fine et al., 2002; Khalil and Rasmussen, 2003).

The second factor was characterized as marine aerosol because of high Cl concentrations. The marine aerosol contribution to PM₁₀ concentrations was 2%, 1%, 4%, and 1% at ABC, GG, Aloft, and CODC, respectively. Marine aerosol is a common component in PM₁₀ throughout New Zealand. The third factor was identified as soil, or crustal matter, and contributed to 1%, 1%, 1%, and 3% of the measured PM₁₀ concentrations at ABC, GG, Aloft, and CODC, respectively. The crustal matter source profile was characterized based on the presence of Al, Si, K, Ca, and Fe. The higher contribution of crustal matter at CODC was likely the result of local roadworks that were taking place near the site. The relatively high concentration of BC in the source profile likely indicates that vehicular movements around the monitoring sites were responsible for resuspending road dust, contributing to a slightly mixed source profile (road dust/crustal matter).

Factor 4 accounted for 11%, 8%, 4%, and 8% of the PM₁₀ mass at ABC, GG, Aloft, and CODC, respectively. This factor was characterized as a vehicular source, which included vehicular exhaust and nonexhaust emissions (road dust). Road dust is generated by the turbulent passage of vehicles over local roads and the source profiles feature crustal elements (Al and Si) enriched with BC, Ca, and Fe. The vehicle source profiles reported here are consistent with those reported previously (Garg et al., 2000; Schauer et al., 2006). Black carbon in the vehicle profiles can be associated with exhaust emissions, deposited tailpipe emissions, and the abrasion of tar-sealed surfaces, and the high concentration of BC in the profile separated this source from the crustal matter source (Factor 3). Iron and copper are typically present in brake wear dust (Thorpe and Harrison, 2008). The higher average contribution from vehicles at ABC is not surprising, since the site was located close to the main road passing through Alexandra. Overall, factors 3 and 4 appear to be closely related to vehicular activities and the distinction between them is not as clear as would generally be expected.

The average hourly source contributions at each site were calculated to assess variations in source contributions on an hourly timescale. Figure 3 presents the average hourly source contributions at GG and Figures S9, S10, and S11 present the average hourly source contributions at ABC, CODC, and Aloft, respectively. A number of notable features are apparent from Figures 2 and S9–S11. First, biomass combustion is a significant PM source every hour during the winter and was responsible for both peaks (evening and morning) observed in the PM₁₀ diurnal cycle. This phenomenon was also observed in Masterton, New Zealand (Ancelet et al., 2012a), and suggests that Alexandra residents are relighting their fires when they rise in the morning. It was suggested by Trompetter et al. (2010) that the morning peak could also result from built-up PM₁₀ above the inversion layer being re-entrained to ground level by atmospheric mixing upon the breakup of the inversion, which has been reported previously (Aryal et al., 2009). Based on measurements from the Aloft site and ground observations (no decreased visibility during the early morning), this mechanism was ruled out. We therefore suggest that katabatic flows result in dispersion and a consequent decrease in PM₁₀ concentrations during the early morning when there are fewer new particle emissions from biomass combustion. The morning peak then arises from fires that are lit or restoked in the morning.

Figure 3. Average hourly source contributions at the Alexandra Girl Guides site.

Source transport

Polar plots using the hourly biomass combustion contributions were prepared to further investigate the transport mechanism and potential biomass combustion source locations. Full descriptions of the processes involved in generating polar plots, including data treatment, have been reported (Carslaw 2012; Carslaw and Rokpins 2012; R Development Core Team, 2011). Using polar plots, the biomass combustion contributions can be plotted as a function of both wind speed and direction. To gain insight into the observed diurnal variations, the source contribution data were divided into night (6 p.m.–8 a.m.) and day (9 a.m.–5 p.m.). It is important to note that the biomass combustion contributions (in μg m⁻³) should not be taken as the actual concentration. The values actually indicate the average concentration for each wind speed/direction bin. Figure 4a and b present biomass combustion polar plots obtained using data from the night and day at the GG site.

Figure 4. Polar plots of biomass combustion contributions during the night (a) and day (b) at the GG site. The radial dimensions indicate the wind speed in 1-msec⁻¹ increments and the color contours indicate the average contribution to each wind direction/speed bin.

Figure 4a shows that during the night, the highest biomass combustion contributions were the result of transport from the northwest when wind speeds were greater than 1 m sec⁻¹, and when wind speeds were very low (<1 m sec⁻¹), some northwest directionality was apparent, with lower contributions also occurring from other directions. Figure 4b also indicates that peak biomass combustion contributions showed some northwest directionality. Under high wind speeds from the west, moderate biomass combustion contributions were also evident during the day. An older residential area with a high concentration of wood burners was west of the GG site, suggesting that at least some homes continued to burn wood throughout the day.

Contributions from vehicular sources at each of the sites increased during peak traffic hours. Vehicle contributions were also apparent during hours when traffic flows would be expected to be minimal. Although Alexandra is a small community, a highway runs through the town and it is likely that heavy-duty diesel vehicles, in particular, provide a consistent PM₁₀ source throughout the day. Further support for this conclusion was provided by polar plots of vehicle contributions during the day and night. Figure S12a and b present polar plots of vehicle contributions during the night and day, respectively. During the day, peak vehicle contributions at GG were transported from the direction of the town center, where local traffic movements during the day would be highest. Overall, vehicle contributions during the day are indicative of local traffic movements along main roads within the town. During the night (Figure S12a), vehicle contributions were largely from the east and northwest. This result suggests that traffic along the highway passing through Alexandra was largely responsible for vehicle contributions during the evening.

Marine aerosol contributions were more pronounced when hourly wind speeds were highest and originated from the south. It is well known that marine aerosol contributions increase under increased wind speeds (Fitzgerald, 1991). Day and night polar plots of marine aerosol and crustal matter contributions are presented in Figures S13 and S14, respectively. Typically crustal matter contributions also increase under increased wind speeds, but Figure S14 indicates that the highest crustal matter contributions occurred during low wind speeds. This suggests that the suspended crustal matter probably originated locally, likely as a result of resuspension by vehicles on local roads where surface silt loadings would be higher than those on higher-traffic roads.

Conclusion

This study aimed to compare PM₁₀ concentrations at four different locations (horizontally and vertically) within an airshed in the rural community of Alexandra, New Zealand. The site locations were upwind, central, and downwind of the general katabatic flow pathway and the fourth site was located centrally, but was raised to 26 m. This type of setup has never been reported before. Hourly, size-resolved (coarse and fine) PM samples were collected at each of the sites and were analyzed for elemental content and BC. The hourly elemental data were used, in combination with PM₁₀ concentrations obtained from E-BAMs co-located with each site, to determine PM sources and their contributions on an hourly timescale. Finally, meteorological data from each of the sites were used to evaluate potential PM transport mechanisms operating in Alexandra.

Diurnal PM₁₀ concentration profiles among the sites showed bimodal patterns, with peak concentrations occurring at different times during the evening and morning depending on the sampling location and diurnal patterns in average wind speeds. The highest PM₁₀ concentrations were measured at the central (GG) site and resulted from the transport of PM₁₀ emitted upwind of general katabatic flows. PM₁₀ concentrations at the elevated site were lower than those at the ground-level site, and in combination with higher wind speeds and temperatures at the elevated site, suggested that the elevated site was located above a shallow inversion layer that limited the vertical dispersion of pollutants.

The application of PMF to the hourly elemental data revealed four PM₁₀ sources at each of the locations: biomass combustion, vehicles, marine aerosol, and crustal matter. Using the average hourly source contributions, plots that identified hourly variations in contributions from different sources were produced. Biomass combustion was found to be the most dominant contributor to both the evening and morning peaks in PM₁₀ concentrations. The dominance of biomass combustion during the morning suggested that Alexandra residents were relighting their fires when they rose in the morning.

Polar plots prepared using source contributions during the day (9 a.m.–5 p.m.) and night (6 p.m.–8 a.m.) revealed a number of interesting features. Elevated biomass combustion contributions at GG during the day and night appeared to be the result of katabatic flows transporting pollutants from areas upwind of the site. Vehicle contributions during the day were shown to arise from traffic movements around the town center and along the main highway through the town. Marine aerosol contributions were highest under high wind speeds from the south. Although crustal matter contributions tend to increase under high wind speeds, we found that the highest crustal matter contributions occurred under low wind speeds, suggesting that resuspension, likely by local traffic, was responsible for elevated crustal matter contributions. The study of PM sources and transport on an hourly timescale provides invaluable information for air quality management and deserves to be studied further.

Supplemental Data

Supplemental data are available for this paper. Go to the publisher’s online edition of the Journal of the Air & Waste Management Association for information containing sampling locations, analytical results, wind and pollution roses, source profiles and source-specific polar plots.

Acknowledgment

The support of Otago Regional Council (Deborah Mills) was greatly appreciated. The authors thank Bruce Crothers and Ed Hutchinson for their support in maintaining the sampling equipment and Chris Purcell for setting up and maintaining the 3-MeV accelerator used for IBA. Stuart Grange is also thanked for his support during sampling.

Funding

This work was funded by the Ministry of Science and Innovation under contract C05X0903.

Additional information

Notes on contributors

Travis Ancelet

Travis Ancelet is a scientist, Perry K. Davy and William J. Trompetter are senior scientists, and Andreas Markwitz is a principal scientist at GNS Science in Lower Hutt, New Zealand.

Perry K. Davy

Travis Ancelet is a scientist, Perry K. Davy and William J. Trompetter are senior scientists, and Andreas Markwitz is a principal scientist at GNS Science in Lower Hutt, New Zealand.

William J. Trompetter

Travis Ancelet is a scientist, Perry K. Davy and William J. Trompetter are senior scientists, and Andreas Markwitz is a principal scientist at GNS Science in Lower Hutt, New Zealand.

Andreas Markwitz

Travis Ancelet is a scientist, Perry K. Davy and William J. Trompetter are senior scientists, and Andreas Markwitz is a principal scientist at GNS Science in Lower Hutt, New Zealand.

David C. Weatherburn

David C. Weatherburn is a senior tutor at Victoria University of Wellington in Wellington, New Zealand.