Mobile monitoring of air pollution in cities: the case of Hamilton, Ontario, Canada

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1 PAPER Journal of Environmental Monitoring monitoring of air pollution in cities: the case of Hamilton, Ontario, Canada Julie Wallace,* a Denis Corr, b Patrick Deluca, a Pavlos Kanaroglou a and Brian McCarry c Received 20th October 2008, Accepted 3rd February 2009 First published as an Advance Article on the web 17th March 2009 DOI: /b818477a Air pollution in urban centres is increasing, with burgeoning population and increased traffic and industry. The detrimental impact on population health has been the focus of many epidemiological studies. Some cities are fortunate to have one, or at most a few, sparsely spaced fixed air quality monitors, which provide much needed daily data. However, fixed monitors do not accurately depict the spatial distribution of air pollution over the extent of an urban area nor can they target areas for focused surveys. We have used mobile monitoring to improve spatial coverage of pollution concentrations over the city of Hamilton, Ontario and to enhance our knowledge of the short-term bursts of pollution to which the population is exposed. surveys have been carried out in the city of Hamilton, Ontario, Canada since Results for two pollutants, oxides of nitrogen (NO x ) representing traffic sources, and sulfur dioxide (SO 2 ) representing industry sources, are presented. The data demonstrate very high levels of NO x exceeding 600 ppb, near major highways with SO 2 levels up to 249 ppb near industrial sources. Both values significantly exceed the hourly maxima recorded by fixed monitors. The results also highlight the effect of wind direction on SO 2 and NO x levels, and the affected population in each scenario. 1. Introduction Air pollution levels in many cities throughout the world have reached alarming levels. Numerous studies have established links to a variety of health outcomes. 1,2 Many jurisdictions employ selected monitoring approaches to ascertain pollutant levels. This paper focuses on mobile monitoring of air pollutants and demonstrates its viability with an application to the city of Hamilton, Ontario, Canada. The main sources of air pollution in Ontario are industry and traffic. Environment Canada 3 estimates that in 2005, industry was responsible for 82% of sulfur dioxide (SO 2 ) emissions, and transportation sources emitted 64% of all oxides of nitrogen (NO x ). Marine and rail sources in Ontario accounted for 4% and 12%, respectively, of the mobile contribution of NO x. 3 Pollution levels are typically measured with fixed ambient air quality monitoring stations, which are usually few in number, and offer limited coverage. Ontario has one of the best networks of fixed ambient air quality monitors in the world, with 37 stations in southern Ontario, operated by the Ontario Ministry of the Environment (MOE). 4 Three of these stations are located in the city of Hamilton, an industrial city which experiences high pollution levels, sometimes exceeding prescribed air quality criteria. 4 The MOE monitors are supplemented by the Hamilton Industrial Air Monitoring Network, a localized system of four a Centre for Spatial Analysis, School of Geography and Earth Sciences, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L8. wallaju@mcmaster.ca b Rotek Environmental Inc., 42 Keefer Court, Unit 2, Hamilton, Ontario, Canada c Department of Chemistry, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4K1 stations serving the main industrial area. The earliest MOE monitors in Hamilton were installed in the 1970s and provide continuous real-time data, as well as valuable long-term trend data, at their location. However, the stations are clustered near the industrial core of the city, and do not capture the spatial contrasts in the urban/rural or industrial/commercial/residential environments. Studies have demonstrated that the pollution concentrations recorded by fixed monitors may not reflect the values of the surrounding areas and therefore are inadequate for assessing population exposure. 5,6 Meta-analysis of several studies 7 suggests that the spatial extent of the impact of mobile sources is of the order of m for particulate matter and m for nitrogen dioxide. Hence, it is clear that monitoring is required close to the source and fixed monitors are insufficient for this purpose. This is particularly relevant to a city such as Hamilton which has a distinct zone of heavy industry in close proximity to older residential surveys and separated geographically from more distant, newer residential surveys. monitoring techniques are a powerful addition to air quality data obtained from fixed monitoring networks but complement fixed monitors, allowing a more complete spatial picture of pollution variability and population exposure. The mobile unit introduces flexibility as it can roam city-wide or be focused on specific locations of concern, such as high-traffic intersections. It can also target problem areas for concentrated surveys and monitor these areas as needed. Because the mobile unit becomes a part of the traffic flow, it is able to quantify the true emissions from vehicles as well as the levels to which other commuters are exposed. 8 Emissions are measured at an instant in time and, for epidemiological studies, may provide better insight into the actual pollution levels with which the exposed human body must contend. The data can thus be useful for investigating 998 J. Environ. Monit., 2009, 11, This journal is ª The Royal Society of Chemistry 2009

2 short-term peak pollution exposure, which can have serious detrimental health impacts With repeated measurements and integration of key factors, such as meteorology and proximity to emission sources, these data can be generalized through statistical techniques to characterize the pollution levels over the surveyed area. 12 data provide a higher spatial resolution product which, combined with the high temporal resolution of fixed continuous monitors, broadens the knowledge of the dispersion of pollution from various sources and city-wide exposure. 13,14 The data may also be used to validate air pollution dispersion models. 15 In this paper, we discuss the application of mobile monitoring in Hamilton, and present some monitoring survey results. In winter 2005, a city-wide mobile survey was initiated, measuring concentrations of SO 2, nitrogen oxide (NO), nitrogen dioxide (NO 2 ), carbon monoxide (CO) and particulate matter of aerodynamic diameter less than 1 mm, 2.5 mm and 10 mm (PM 1,PM 2.5 and PM 10, respectively). The surveys are ongoing. The data presented here will be restricted to SO 2 representing emissions from industry, and NO x which is typically a marker for traffic emissions. Examples from city-wide surveys conducted between 2005 and 2007 will be used to demonstrate the advantages of mobile surveys in assessing spatial variability of air pollution across the city and in mapping population exposure. The impact of SW prevailing winds and secondary NE winds on the population is also presented. 2. Study area Hamilton, Ontario is situated at the western tip of Lake Ontario (43.3 N, 79.9 W) and hosts a population of approximately (Fig. 1). This medium-sized city provides a good test area for the effects of air pollution as it has a wide range of emitters which include two major steel companies with associated heavy and mixed industry, a university and several hospitals. Although the most visible heavy industries are located on Hamilton s sheltered natural harbour in the northeastern section of the city, five different industrial areas are identifiable (Fig. 1). The city also accommodates many modes of transportation, with major rail and highway corridors linking the Greater Toronto conurbation to the United States, as well as high cargo flows in the harbour. Four major highways are channelled through the city which also has a busy local street network. The Niagara Escarpment divides the city into an upper and lower sector, with several satellite villages incorporated in the larger urban area. Prevailing winds are from the southwest. However, lake effect winds from the northeast and atmospheric inversion conditions can cause pollutant buildups, particularly in the lower city. Hamilton has grown approximately 7.9% between 1996 and 2006 (Statistics Canada, 2007). 16 Growth has occurred primarily along the periphery of the city, increasingly away from the existing fixed monitors. In addition, transportation corridors are being expanded in newly developed areas, adding to the relevance of mobile monitoring throughout the city. 3. Methodology Instruments The mobile monitoring unit consists of an enclosed van (Fig. 2) equipped with pollution monitors, a GPS unit, and a laptop, all powered by an integrated battery pack which provides power for over 4 h of sampling. Fig. 1 City of Hamilton: major roads, land use and industry sources of pollution. This journal is ª The Royal Society of Chemistry 2009 J. Environ. Monit., 2009, 11,

3 fixed air monitoring network. This was then used in nrouteô to identify pollutant sources and impact distance. Pollution data were recorded every second. Data collection procedures Fig. 2 monitoring unit. The pollution monitors include a TECOÔ Model 42C NO x analyzer (range ppm), a Monitor LabsÔ 8850 SO 2 analyzer (range ppm), a TECOÔ Model 48 CO analyzer (range ppm) and a GrimmÔ Model Dust Monitor (range mg/m 3 ) which is capable of simultaneous measurement of PM 1,PM 2.5 and PM 10. A separate sampling pump provides appropriate airflow for the gas analyzers. All monitors are accurate to 1 ppb except the CO analyzer which is accurate to 1 ppm and the GrimmÔ particulate monitor which is accurate to 1 mg/m 3. The CO and NO x monitors were calibrated using certified gas mixtures obtained from BOC Canada (now Linde Canada Limited). An ESA Model VE-3M sulfur dioxide calibrator was used for the sulfur dioxide monitor. The Grimm particulate monitor was calibrated using the Grimm X78502 Dust Tower calibration system at Rotek Environmental Inc., Hamilton, Ontario, the manufacturer s official Canadian calibration site for these instruments. Zero air was provided by an Environmental Systems Corporation 770P Zero Air Generator. Ambient air for the gaseous analyzers was sampled through a specially constructed gooseneck sampling head which passed through the roof of the vehicle with a rain shield attachment, to prevent precipitation entering the system. Sampling intake height was approximately 3 m above ground level to mitigate instantaneous fluctuations in pollutant concentrations due to tailpipe emissions. Teflon tubing of ¼ inch diameter with particle prefilters was used to distribute the incoming air to the gas analyzers. The GrimmÔ Dust Monitor was mounted separately and modified with a 2 m long sampling intake to reach through the vehicle roof. Positional information was captured through a roof-mounted GarminÔ GPS16-HVS detector with 1 s temporal resolution. A second GPS unit attached to the vehicle windshield (GarminÔ 18 laptop-enabled GPS) was used as a backup. All pollution and GPS data were collected simultaneously using a Campbell 23X data logger, and stored in an integrated database. Garmin nrouteô software was used for route planning and data visualization during sampling. GPS waypoints with comments and the bearing from selected locations were recorded. This proved useful for back trajectories, plume tracking and noting localized effects such as diesel exhaust from idling trucks. When a pollution impact was recorded by the monitoring system, wind direction was later downloaded from a local wind monitor in the A standardized data collection procedure was developed for the survey. First, the laptop was installed in the vehicle and connected to the GPS unit. The nrouteô software was then initiated so that the vehicle position and the associated time could be recorded. The data logger was checked to ensure proper working order and the sampling plan reviewed. Once the sampling route began, the technician notified the driver of instantaneous outliers in the pollution data collected, and simultaneously marked waypoints in nrouteô. Comments were recorded in a separate data log book to indicate possible causes of the outlier. In all instances where outliers were detected, the route was retraced as slowly as possible. The unit was halted in areas of hot spots to allow more accurate data capture and where possible, both upwind and downwind directions of suspected sources were monitored. Route planning Sampling was conducted under various meteorological conditions to determine the impacts across the city. Prevailing SW winds place the city upwind of industrial sources, though the city remains affected by vehicular emissions and re-suspended particulate matter from roads and highways. Under NE wind conditions, with resulting light temperature inversions and lake breezes, heavy industry impacts a large section of the city. traverses were conducted from the relatively rural southwest end of the city towards and through the industrial sector, and in the reverse direction from the industrial northeast end to the southwest. Sampling points were also established in the centre of city blocks and away from the direct influence of traffic emissions on major roads, in order to characterize pollutant levels in residential areas. Data processing and analysis Post-processing of the route and pollutant data was carried out to remove spurious or errant values and the data were converted to a format compatible with ArcGIS 9.2 software. 17 The high density of data resulting from second-to-second data recording presented a problem in mapping unique coordinate points, and the data required filtering to extract unique x y coordinates. Each x y coordinate location with associated pollution attributes was mapped as point locations. While concentrations of SO 2, NO, NO 2,NO x, CO, PM 1,PM 2.5 and PM 10 were recorded in the database, data for SO 2 and NO x only were extracted for this discussion, in order to illustrate the effects of industry and traffic, respectively. Hourly wind direction and wind speed were obtained from local meteorological stations and integrated with the pollution data. All data collected between 2005 and 2007 were aggregated and then separated according to SW and NE wind directions. The final database represented 16 days of mobile surveys, nine conducted on NE wind days and seven on SW wind days J. Environ. Monit., 2009, 11, This journal is ª The Royal Society of Chemistry 2009

4 Table 1 Summary statistics for SO2 and NOx on SW and NE wind days compared to 1 h average and maximum values measured at Ontario Ministry of the Environment fixed monitors Wind direction SW NE SW NE Pollutant SO2 NOx minimum (ppb) maximum (ppb) average (ppb) std dev MOE 1 h average (ppb) MOE 1 h maximum (ppb) Results and discussion Aggregated SO2 concentrations from the surveys, ranged from ppb with an average of 9 ppb, for prevailing SW wind days (Table 1). The highest values were confined to areas in close proximity to major industries on Hamilton Harbour, to downwind locations along the Queen Elizabeth Way (QEW) and the northern shore of Hamilton Harbour (Fig. 3). On SW wind days, most of the city lies upwind of the industrial zone, and hence is largely protected from SO2 transported from local industries. Concentrations are typically 10 ppb or less. However, exposure in sections of the lower city, which are in close proximity to industry, is more significant. On NE wind days, concentrations ranged from ppb with an average of 13 ppb. Highest values were located in close proximity to industries but also extended downwind into residential neighbourhoods abutting the Niagara Escarpment in the lower city (Fig. 4). The lower section of the city as well as valleys, such as the Dundas Fig. 4 Sulfur dioxide concentrations on traverses throughout the city under NE wind conditions. Fig. 3 Sulfur dioxide concentrations on traverses throughout the city under prevailing SW wind conditions. This journal is ª The Royal Society of Chemistry 2009 Valley, is most vulnerable on NE wind days, experiencing levels of 50 ppb or greater. NOx concentrations on SW wind days ranged from ppb, with an average of 62 ppb (Table 1). Highest values were confined to major highways, particularly the Hwy 403 links over Hamilton Harbour, and near the Lincoln Alexander Parkway (Fig. 5). These highways, in particular the QEW and Hwy 403, are major truck transportation corridors linking the Greater Toronto Area with the US and southwestern Ontario. Trucks contribute a substantial portion of the NOx emissions on highways. Other streets with high NOx levels include local city streets which link to the QEW at the southeast end of the city (Fig. 5). These streets are located close to the industrial zone which generates increased local traffic and are also close to residential zones. On NE wind days, NOx concentrations range from ppb with an average of 46 ppb. The highest values are located along Hwy 403, just north of the Lincoln Alexander Highway. Other J. Environ. Monit., 2009, 11,

5 Fig. 5 Concentrations of nitrogen oxides on traverses throughout the city under prevailing SW wind conditions. Fig. 7 NOx daily monitoring track for March 9, 2007 with winds from the NE. Fig. 6 Concentrations of nitrogen oxides on traverses throughout the city under NE wind conditions. high values are located in the western end of the city close to the Niagara Escarpment as well as along major streets which parallel the base of the escarpment (Fig. 6). Fig. 7 shows an example of a daily track for NOx on a single day, March 9, 2007, with winds from the northeast. The impact of major highways, particularly Hwy 403, with NOx values ranging up to 621 ppb on this day, is evident. Traffic on major roads which feed into the main highways is also a source of high NOx, and levels are reduced within residential areas which are not in close proximity. For both wind directions, proximity to highway is the major factor in NOx concentrations, with the more distant residential areas experiencing lower levels, typically 50 ppb or less. The mobile data were compared to concentrations recorded by a fixed continuous ambient air quality monitoring station located in lower Hamilton (43.26 N, W). This monitor is maintained by the MOE and the values represent average and maximum hourly data, averaged over the period (Table 1). The averaged MOE values are, as expected, lower than the instantaneous values gathered by the mobile monitoring unit. The differences result, in part, from two factors. First, the MOE data represent averages for two years of continuous monitoring and include diurnal and seasonal variations, while the mobile data represent averages of point concentrations recorded in the daytime, on weekdays. These instant in time data are subject to high variability as they are affected by the moment-to-moment activity in the city, and the location of the mobile unit at that point in time. These data are extremely valuable, however, as they reflect the true exposure of the population as they engage in daily life activities. The second factor which influences the differences between the fixed and mobile data relates to the 1002 J. Environ. Monit., 2009, 11, This journal is ª The Royal Society of Chemistry 2009

6 spatial coverage of each. The MOE data reflect concentrations over limited spatial extent within the confines of the point location of the monitor, while the roaming mobile survey captures concentrations across the entire survey area. The mobile data therefore provide a more realistic perspective on population exposure as well as on pollution sources. The high temporal density of the mobile data (recorded every second) increases data accuracy and spatial coverage on the surveyed route. The mobile data are indicative not only of the large spatial variability across the city but also of the temporal variations from moment to moment. 5. Conclusions As with many industrial cities in the world, Hamilton has localized areas of heavy industry, a broad traffic network and a population which is dispersed across the city, some affected by industry pollution, some primarily by traffic pollution, and others by both. A few sparsely placed monitors do not adequately characterize the level of exposure of all residents. Studies have shown that close proximity to roads, that is within 300 m, is the zone of greatest health impact and it is therefore important to assess the pollution levels in these areas. surveys provide the most effective methods of achieving this. They have also afforded a better understanding of dispersion of industry pollutants under various meteorological scenarios, and hence, the potential effect on residents living within high impact areas. Within the complexity of a cityscape buildings, bridges, tunnels, trees and so on as well as uncertainties in meteorological models and coarse spatial resolution, air quality and dispersion modeling often do not capture every nuance of the pollution concentrations across the city. A critically important aspect of mobile surveys is that the data depict exposure at a point in time. It may be argued that, apart from a personal monitoring system worn by an individual, mobile surveys more accurately convey the pollution levels to which individuals at a location are exposed in the short term. These levels would be more significant for analysis of short-term exposure than the currently available fixed network hourly maxima or averages. For example, while a fixed monitor may record a maximum 1 h value of 250 ppb for NO x on a given day, we have recorded values in excess of 600 ppb in some locations. This clearly affirms that individuals are exposed to much higher levels than stipulated by fixed air quality monitors, and these levels may be more pertinent to epidemiological studies and the human body s immediate reaction to such high bursts of pollution. It is also of significance that a variety of pollutants are recorded, as the toxic mix of many pollutants may be more consequential than exposure to any single pollutant, as is sometimes the case in laboratory experiments. We have shown definitively the impact of wind direction on pollution levels, particularly from industry, over the city. As expected, the surveys have identified the major highways as the primary sources of NO x, with proximity to highways being the most significant factor in concentration levels. However, the extent of the high concentrations was unexpected and warrants concern for persons who spend considerable time in traffic and particularly, in congested traffic. Concentrations in residential areas are relatively low, averaging less than 50 ppb NO x and 10 ppb SO 2. Both values are well below the 1 h ambient air quality criteria for NO 2 which is 200 ppb and for SO 2 which is 250 ppb. 4 However, NO x levels rise steeply on arterial roads, and are highest on highways with frequent heavy duty truck traffic. These surveys have provided a more accurate depiction of the population exposure to health impacting air pollutants. Heavy industry is very visible in Hamilton and is often assumed to be the major source of air pollution in the city. However, these data show that highest concentrations and hence the highest levels of exposure of nearly all residents result from vehicle emissions. The results can also be applied in siting locations for future fixed monitoring stations, as the population grows and the city expands. These results have significant relevance for public health, municipal planning and public policy and will be useful in epidemiological studies. surveys can be conducted in any location with road infrastructure and may help to improve assessment of population exposure in high pollution areas. This is particularly important in areas where there is a spatial differential in source emissions, such as regions with localized industries and a dispersed road network over a sprawled urban area. Acknowledgements We would like to thank Clean Air Hamilton, the City of Hamilton, Ontario Ministry of the Environment and GeoConnections for financial and in-kind support of this project. References 1 A. Peters and C. A. Pope III, Lancet, 2002, 360, A. J. Cohen, H. R. Anderson, B. Ostra, K. D. Pandey, M. Krzyzanowski, N. K unzli, K. Gutschmidt, A. Pope, I. Romieu, J. M. Samet and K. Smith, J. Toxicol. Environ. 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