DS-14-118

wwvvi scorgjern I Journal of Environmental Monitoring

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

Julie Wallace Denis Corrb Patrick Deluca a Pavlos Kanaroglou and Brian McCarryc

Received 20th October 2008 Accepted 3rd Fehrnary 2009 Ffr~t published as a11 Ad1ia11ce Article 011 the web 17th March 2009

DOI 101039b818477a

A ir pollution in urban centres is increasing with burgeoning population and increased traffic and industry The detrimenta l impact on population health has been the focus of many epidemiological studies Some cit ies are fortunate to have one or at most a few sparsely spaced fixed air quality monitors which provide much needed daily data However fixed moni tors do not accurately depict the spatial distribution of air pollution over the extent of a n 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 pollut ion to which the population is exposed Mobile surveys have been carried out in the city of Hamilton Ontario Canada since 2005 Results for two pollutants oxides of nitrogen (NOx representing traffic sources and sulfur dioxide (S02) representing industry sources are presented The da ta demonstrate very high levels ofNOx exceeding 600 ppb near major highways with S02 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 ofwind direction on S02 and NO levels and the affected population in each scenario

1 Introduction stations serving the main industrial area The earliest MOE monitors in Hamilton were installed in the 1970s and provide

Air pollut ion levels in many cities throughout the world have continuous real-time data as well as valuable long-term trend reached alarming levels Numerous studies have established links data at their location However the stations are clustered near to a variety of health outcomes- Many jurisdictions employ the industrial core of the city and do not capture the spatial selected monitoring approaches to ascertain pollutant levels contrasts in the urbanrural or industrialcommercialresidential This paper focuses on mobile monitoring of air pollutants and environments Studies have demonstrated that the pollution demonstrates its viability with an application to the city of concentrations recorded by fixed monitors may not reflect the Hamilton Ontario Canada values of the surrounding areas and therefo re are inadequate for

The main sources of air pollution in Ontario are industry and assessing population exposure middot6 Meta-analysis of several traffic Environment Canada 3 estimates that in 2005 industry studies7 suggests that the spatial extent of the impact of mobile was responsible for 82 of sulfur dioxide (S02) emissions and sources is of the order of 100-400 m for particulate matter and transportation sources emitted 64 of all oxides of nitrogen 200- 500 m for nitrogen dioxide Hence it is clear that monishy(NOx) Marine and rail sources in Ontario accounted for 4 and toring is required close to the source a nd fixed monitors are 12 respectively of the mobile contribution of NOx 3 Pollution insufficient for this purpose This is particula rly relevant to a city levels are typically measured with fixed ambient air quality such as Hamilton which has a distinct zone of heavy industry in monitoring stations which a re usually few in number and offer close proximity to older residential surveys and separated limited coverage Ontario has one of the best networks of fixed geographically from more distant newer resident ial surveys ambient a ir quality monitors in the world with 37 stations in Mobile monitoring techniques are a powerful addition to air southern Ontario operated by the Ontario Ministry of the quality data obtained from fixed monitoring networks but Environment (MOE)4 Three of these stations are located in the complement fixed monitors allowing a more complete spa tial city of Hamilton an industrial city which experiences high picture of pollution varia bility and population exposure The pollution levels sometimes exceeding pre5cribed air quality mobile unit introduces flexibility as it can roam city-wide or be criteria4 The MOE monitors are supplemented by the Hamilton focused on specific locations of concern such as high-traffic Industrial Air Monitoring Network a localized system of four intersections It can also target problem areas for concentrated

surveys and monitor these areas as needed Because the mobile

Centre for Spa1ial Analysis School of Geography and Earih Sciences unit becomes a part of the traffic flow it is able to quantify the McMaster Universi1_1 middot 1280 Main Street West Hamilton Ontario true emissions from vehicles as well as the levels to which othermiddot Ca11ada L8S 4L8 E-mail 111allai11mcmasterca commuters are exposed8 Emissions are measured at an instant in R orek Enviromnenral Inc 42 Keefer Courr Unit 2 H ami1011 Omario time and for epidemiological studies may provide better insight Canada bullDeparrmenr of Chemistry AcMasrer UniversiT) 1280 Main Srreer Wesr into the actual pollution levels with which the exposed human Hamilton Onrario Ca11ada L8S 4Kl body must contend The data can thus be useful fo r investigating

998 I J Environ Monit 2009 1 1 998-1 003

wwvvi scorgjern I Journal of Environmental Monitoring

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

Julie Wallace Denis Corrb Patrick Deluca a Pavlos Kanaroglou and Brian McCarryc

Received 20th October 2008 Accepted 3rd Fehrnary 2009 Ffr~t published as a11 Ad1ia11ce Article 011 the web 17th March 2009

DOI 101039b818477a

A ir pollution in urban centres is increasing with burgeoning population and increased traffic and industry The detrimenta l impact on population health has been the focus of many epidemiological studies Some cit ies are fortunate to have one or at most a few sparsely spaced fixed air quality monitors which provide much needed daily data However fixed moni tors do not accurately depict the spatial distribution of air pollution over the extent of a n 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 pollut ion to which the population is exposed Mobile surveys have been carried out in the city of Hamilton Ontario Canada since 2005 Results for two pollutants oxides of nitrogen (NOx representing traffic sources and sulfur dioxide (S02) representing industry sources are presented The da ta demonstrate very high levels ofNOx exceeding 600 ppb near major highways with S02 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 ofwind direction on S02 and NO levels and the affected population in each scenario

1 Introduction stations serving the main industrial area The earliest MOE monitors in Hamilton were installed in the 1970s and provide

Air pollut ion levels in many cities throughout the world have continuous real-time data as well as valuable long-term trend reached alarming levels Numerous studies have established links data at their location However the stations are clustered near to a variety of health outcomes- Many jurisdictions employ the industrial core of the city and do not capture the spatial selected monitoring approaches to ascertain pollutant levels contrasts in the urbanrural or industrialcommercialresidential This paper focuses on mobile monitoring of air pollutants and environments Studies have demonstrated that the pollution demonstrates its viability with an application to the city of concentrations recorded by fixed monitors may not reflect the Hamilton Ontario Canada values of the surrounding areas and therefo re are inadequate for

The main sources of air pollution in Ontario are industry and assessing population exposure middot6 Meta-analysis of several traffic Environment Canada 3 estimates that in 2005 industry studies7 suggests that the spatial extent of the impact of mobile was responsible for 82 of sulfur dioxide (S02) emissions and sources is of the order of 100-400 m for particulate matter and transportation sources emitted 64 of all oxides of nitrogen 200- 500 m for nitrogen dioxide Hence it is clear that monishy(NOx) Marine and rail sources in Ontario accounted for 4 and toring is required close to the source a nd fixed monitors are 12 respectively of the mobile contribution of NOx 3 Pollution insufficient for this purpose This is particula rly relevant to a city levels are typically measured with fixed ambient air quality such as Hamilton which has a distinct zone of heavy industry in monitoring stations which a re usually few in number and offer close proximity to older residential surveys and separated limited coverage Ontario has one of the best networks of fixed geographically from more distant newer resident ial surveys ambient a ir quality monitors in the world with 37 stations in Mobile monitoring techniques are a powerful addition to air southern Ontario operated by the Ontario Ministry of the quality data obtained from fixed monitoring networks but Environment (MOE)4 Three of these stations are located in the complement fixed monitors allowing a more complete spa tial city of Hamilton an industrial city which experiences high picture of pollution varia bility and population exposure The pollution levels sometimes exceeding pre5cribed air quality mobile unit introduces flexibility as it can roam city-wide or be criteria4 The MOE monitors are supplemented by the Hamilton focused on specific locations of concern such as high-traffic Industrial Air Monitoring Network a localized system of four intersections It can also target problem areas for concentrated

surveys and monitor these areas as needed Because the mobile

Centre for Spa1ial Analysis School of Geography and Earih Sciences unit becomes a part of the traffic flow it is able to quantify the McMaster Universi1_1 middot 1280 Main Street West Hamilton Ontario true emissions from vehicles as well as the levels to which othermiddot Ca11ada L8S 4L8 E-mail 111allai11mcmasterca commuters are exposed8 Emissions are measured at an instant in R orek Enviromnenral Inc 42 Keefer Courr Unit 2 H ami1011 Omario time and for epidemiological studies may provide better insight Canada bullDeparrmenr of Chemistry AcMasrer UniversiT) 1280 Main Srreer Wesr into the actual pollution levels with which the exposed human Hamilton Onrario Ca11ada L8S 4Kl body must contend The data can thus be useful fo r investigating

998 I J Environ Monit 2009 1 1 998-1 003

middot

J

i

r-~---- ~

middot-

Map Key C) tndustriat sites

bull MOEFixed Montors

-- Expressway bull Maj-OJ Road ~middot--]

RuralAteas

Fig I City of Hamilton major roads land use and industry sources of pollution

J Environ Monit 2009 11 998-1003 999

short-term peak pollution exposure which can have serious 500 000 (Fig I) This med ium-sized city provides a good test area detrimental health impactsgt- With repeated measurements and for the effects of air pollution as it has a wide range of emitters integration of key factors such as meteorology and proximity to which include two major steel companies with associated heavy emission sources these data can be generalized through statisshy and mixed industry a university and several hospi tals Although tical techniques to characterize the pollution levels over the the most visible heavy industries are located on Hamiltons surveyed area12 Mobile data provide a higher spatial resolution sheltered natural harbour in the northeastern section of the city product which combined with the high temporal resolution of five different industrial areas are identifiable (Fig I) T he city fixed continuous monitors broadens the knowledge of the also accommodates many modes of transportation with major dispersion of pollution from various sources and city-wide rail and highway corridors linking the Greater Toronto conurshyexposureubullbull The data may also be used to validate air pollution bation to the United States as well as high cargo flows in the dispersion models 15 harbour Four major highways are channelled through the city

Jn this paper we d iscuss the application of mobile monitoring which also has a busy local street network The N iagara in Hamilton and present some monitoring survey results In Escarpment divides the city into an upper and lower sector with winter 2005 a city-wide mobile survey was initiated measuring several satell ite villages incorporated in the larger urban area concentrations of S0 2 nitrogen oxide (NO) nitrogen dioxide Prevailing winds are from the southwest However lake e ffect (N 0 2) carbon monoxide (CO) and particulate matter of aeroshy winds from the northeast and atmospheric inversion conditions dynamic diameter less than I microm 25 microm and 10 microm (PM1 PM25 can cause pollutant buildups particularly in the lower city and PM 10 respectively) The surveys arc ongoing The data Hamilton has grown approximately 79 between 1996 and presented here wi ll be restricted to S0 Canada 2007) 6

2 representing emissions 2006 (Statistics Growth has occurred primarily from industry and NOx which is typically a marker for traffic along the periphery of the city increasingly away from the emissions Examples from city-wide surveys conducted between existing fixed monito rs In addition transportation corridors are 2005 and 2007 will be used to demonstrate the advantages of being expanded in newly developed areas adding to the releshymobile surveys in assessing spatial variability of a ir pollution vance of mobile monitoring throughout the city across the city and in mapping population exposure The impact of SW prevail ing winds and secondary NE winds on the popshy 3 Methodology ulation is also presented

Instruments

The mobile monitoring unit c-0nsists of an enclosed van (Fig 2) 2 Study area equipped with pollution monitors a GPS unit and a laptop all

Hamilton Ontario is situated at the western tip of Lake Ontario powered by an integrated battery pack which provides power for (433deg N 799deg W) and hosts a population o f approximately over 4 h of sampling

Fig 2 Mobi le monitoring unit

T he pollution monitors include a TECOtrade Model 42C NOshyanalyzer (range 0- 100 ppm) a Monitor LabsTM 8850 S02

analyzer (range 0-100 ppm) a TECQTM Model 48 CO analyzer (range 0-10 000 ppm) and a GrimmTM Model 1107 Dust Monitor (range 1-6500 microgm 3

) which is capable of simultaneous measurement of PM1 PM25 and PM10 A separate sampling pump provides appropriate airflow for the gas analyzers All monitors are accurate to I ppb except the CO analyzer which is accurate to I ppm and the GrimmTM particulate monitor which is accurate to I ~1glm-

The CO and NO 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 calibrat ion system at Rotek Environmental lnc Hamilton Ontario the manufacturers 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 instanshytaneous fluctuations in pollutant concentrations due Lo tailpipe emissions Teflon tubing of Y inch diameter with particle preshyfilters was used to distribute the incoming air to the gas analyzers The G rimmrn 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 GarminT GPS16-HVS detector with I s temporal resolution A second GPS unit attached to the vehicle windshield (Garmin TM 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 nRouteTM software was used for route planning and data visushyalization during sampling GPS waypoints with comments and the bearing from selected locations were recorded This p roved useful for back trajectories plume tracking and noting localized effects such as diesel exhaust from idling trucks When a pollushytion impact was recorded by the monitoring system wind direction was later downloaded from a local wind monitor in the

fixed air monitoring network This was then used in nRoutenlt to identify pollutant sources and impact distance Pollution data were recorded every second

Data collection procedures

A standardized data collection procedure was developed rorfU1e survey First the laptop was installed in the vehicle and co~shynected to the GPS unit The nRouteTM software was then initiated so that the vehicle position and the associated time could be recorded The data Jogger was checked to ensure proper work ing 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 mark~d waypoints in nRoute1middot 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 T he unit was halted in areas ofhot 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 condishytions 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 Mobile traverses were conducted from the rela tively 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 resishydential 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 ArcGJS 92 software 7 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 associa ted pollution attrishybutes was mapped as point locations While concentrations of S02 NO N02 NO CO PM1 PM2s and PM1o were recorded in the database data for S02 and NOx only were extracted for this discussion in order to illustrate the elTccts of indus try 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 N1i wind directions The fina l database represented 16 days of mo bi Iii surveys nine conducted on NE wind days and seven on SW wi1Jtti days

1000 I J Environ Monit 2009 11 998-1003

Fig 2 Mobi le monitoring unit

T he pollution monitors include a TECOtrade Model 42C NOshyanalyzer (range 0- 100 ppm) a Monitor LabsTM 8850 S02

analyzer (range 0-100 ppm) a TECQTM Model 48 CO analyzer (range 0-10 000 ppm) and a GrimmTM Model 1107 Dust Monitor (range 1-6500 microgm 3

) which is capable of simultaneous measurement of PM1 PM25 and PM10 A separate sampling pump provides appropriate airflow for the gas analyzers All monitors are accurate to I ppb except the CO analyzer which is accurate to I ppm and the GrimmTM particulate monitor which is accurate to I ~1glm-

The CO and NO 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 calibrat ion system at Rotek Environmental lnc Hamilton Ontario the manufacturers 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 instanshytaneous fluctuations in pollutant concentrations due Lo tailpipe emissions Teflon tubing of Y inch diameter with particle preshyfilters was used to distribute the incoming air to the gas analyzers The G rimmrn 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 GarminT GPS16-HVS detector with I s temporal resolution A second GPS unit attached to the vehicle windshield (Garmin TM 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 nRouteTM software was used for route planning and data visushyalization during sampling GPS waypoints with comments and the bearing from selected locations were recorded This p roved useful for back trajectories plume tracking and noting localized effects such as diesel exhaust from idling trucks When a pollushytion impact was recorded by the monitoring system wind direction was later downloaded from a local wind monitor in the

fixed air monitoring network This was then used in nRoutenlt to identify pollutant sources and impact distance Pollution data were recorded every second

Data collection procedures

A standardized data collection procedure was developed rorfU1e survey First the laptop was installed in the vehicle and co~shynected to the GPS unit The nRouteTM software was then initiated so that the vehicle position and the associated time could be recorded The data Jogger was checked to ensure proper work ing 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 mark~d waypoints in nRoute1middot 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 T he unit was halted in areas ofhot 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 condishytions 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 Mobile traverses were conducted from the rela tively 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 resishydential 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 ArcGJS 92 software 7 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 associa ted pollution attrishybutes was mapped as point locations While concentrations of S02 NO N02 NO CO PM1 PM2s and PM1o were recorded in the database data for S02 and NOx only were extracted for this discussion in order to illustrate the elTccts of indus try 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 N1i wind directions The fina l database represented 16 days of mo bi Iii surveys nine conducted on NE wind days and seven on SW wi1Jtti days

1000 I J Environ Monit 2009 11 998-1003

Table I Summary statistics for S02 and NO_ on SW and NE wind days compared to l h average and maximum va lues measured at Ontario Min istry of the Environment fixed monitors

MOE I h MOE I h Wind Mobile Mobile Mobi le Mobile average maximum direction Pollutant minimum (ppb) maximum (ppb) average (ppb) std dev 2005shy 2006 (ppb) 2005-2006 (ppb)

SW S02 l 109 94 4 51 85 NE 0 249 13 12 SW NO 3 600 62 54 274 404 ~

NE 3 621 46 40

4 Results and discussion

Aggregated S02 concentrations from the 2005- 2007 surveys ranged from 1-109 ppb with an average of9 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 S02 transported from local industries Concentrations are typically 10 ppb or less However exposure in sections of the lower city which are in close proxshyimity to industry is more significant On NE wind days concentrations ranged from 0-249 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

Legend

Majo Ro3lt1i and HvYS

0 2 with SW winds (ppb) shybull 1 middot 1() -

11 20

11 middotmiddot4~

41-- 8()

Fig 3 Sulfur dioxide co11ccntra tio11s on traverses thro ughout the city under prevailing SW wind condit ions

Legend

M~joRoads aod iibull)s

0 2 with NE winds (ppb) bull 0-10

bull 11-20

~middot1 40

41eo

bull e1 24

Lake Omanc

Fig 4 SuJfur dioxide concentrations on traverses througho ut the city under NE wind conditions

Valley is most vulnerable on NE wind days experiencing levels of 50 ppb or greater

NOx concentrations on SW wind days ranged from 3- 600 ppb with an average of 62 ppb (Table l) 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 highshyways 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 a re also close to residential zones

On NE wind days NOx concetJtrations range from 3- 621 ppb with an average of 46 ppb The highest values are localed along Hwy 403 just north of the Lincoln Alexander Highway Othermiddot

J Environ Monit 2009 11 998-1 003 J 1001

Legend

MaiCY RoddS atd Hv11

NO with SW w inds (ppb) ~ 3 - 50

51 middot ~00

1M middot200

2ii 400

lake On1irio

Fig S Co ncentrat ions of n itrogen oxides on traverses throughout the city under prevailing SW wind conditions

Legend

NO with NE winds (ppb ~ 0 - 50

51 ~ 100

101 200

bullmiddot 201 - 400

Fig 6 Concentrations of n itrogen oxides on traverses throughout the city under NE wind conditions

1002 I J Environ Monit 2009 11 998- 1003

Legend

fiPjor Roads ard Hw)bulls

o (ppb) with NE winds March 9 2007

O middotn so 0 51-100

0 1-01 - 200

0 201- 400

e 401 - 621

iafee Olilano

Fig 7 NOx da ily moniloring track for March 9 2007 with winds from the NE

high values are located in the western end of the city close to the Niagara Escarpment as well as a long major streets which parallel the base of the escarpment (Fig 6) F ig 7 shows an example of a daily track for NOr on a single day March 9 2007 with winds from the northeast The impact of major highways particularly Hwy 403 with NO values ranging up to 621 ppb on this day is evident Traffic on major roads which feed into the main highshyways 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 experishyencing lower levels typically 50 ppb or less

The mobile data were oompared to concentrations recorded by a fixed cont inuous ambient air quality monitoring station located in lower Hamilton (4326deg N 7986deg V) This monitor is mainshytained by the MOE and the values represent average and maximum hourly data averaged over the period 2005- 2006 (Table I) The averaged MOE values are as expected lower than the instantaneous values gathered by the mobile monitoring unit The di fferences result in part from two factors First the MOE data represent averages for two years of continuous monitoring and include diurnal and seasonal variat ions while the mobile data represent averages of point concentrations recorded in the daytime o n weekdays These instan t in time data are subject to h igh variability as they a re affected by the moment-to-moment activi ty 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 act ivities The second facto r which influences the difference$ between the fi xed and mobile data relates t~ the

spatial coverage of each The MOE data reflect concentrations over limi ted spatial extent within the confines of the point locashyt ion of the monitor while the roaming mobile survey captures concentrations across the entire survey area The mobile data t herefore provide a more realistic perspective on population exposure as well as on pollution sources The high temporal density of the mobi le 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 a lso of the temporal variations from moment to moment

5 Conclusions

As with many indust rial cities in the world Hamilton has localized areas o f 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 wi thin 300 m is the zone of greatest health impact and it is therefore important to assess the pollution levels in these areas Mobile 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 wel l as uncertainties in meteoroshylogical 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 1t 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 networ k hourly maxima or averages F or example while a fixed monitor may record a maximum l h value of 250 ppb for NOx 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 bodys immediate reaction to such high bursts of pollution It is also of significance tl1a t a variety of pollutan ts are recorded as the toxic mix of many poll utants may he more consequential than expo shysure to any single pollutant as is sometimes the case in laborashytory 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 NOltgt 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 pa rticularly in congested traffic Concentrations in residential areas are relatively low averaging less t han 50 ppb NOx and

10 ppb S02 Both values are well below the I h ambient a ir quality criteria for N02 which is 200 ppb and for S02 which is 250 ppb4 However NOx 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 visib le 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 middot exposure of nearly a ll residents resu lt 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 Mobile 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 diITershycntial in source emissions such as regions with local ized indusshytries and a dispersed road networ k over a sprawled urban area

Acknowledgements

We would like to thank Clean Air Hamilton the City of Hamshyilton Ontario Ministry ofthe Environment and GeoConnections

middot for financial and in-kind support of this project

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15 J Wa llace and P Kanaroglou Tra11sporratio11 Research Pltlrl D 2008 13 323- 333

16 Statistics Canada 2007 Community Profiles 2006 Census S tatistics Canada Catalogue no 92-591-XWE Ottawa httpwwwl2s tatcan cacensusmiddotrecensement2006dp-pdprof92-591 indexcfm accessed June 30 2008

17 ArcGIS version 9x Environmental Systems Research Inc (ESRJJ Redlands California 2008

J Environ Monit 2009 11 998- 1003 I 1003

Legend

MaiCY RoddS atd Hv11

NO with SW w inds (ppb) ~ 3 - 50

51 middot ~00

1M middot200

2ii 400

lake On1irio

Fig S Co ncentrat ions of n itrogen oxides on traverses throughout the city under prevailing SW wind conditions

Legend

NO with NE winds (ppb ~ 0 - 50

51 ~ 100

101 200

bullmiddot 201 - 400

Fig 6 Concentrations of n itrogen oxides on traverses throughout the city under NE wind conditions

1002 I J Environ Monit 2009 11 998- 1003

Legend

fiPjor Roads ard Hw)bulls

o (ppb) with NE winds March 9 2007

O middotn so 0 51-100

0 1-01 - 200

0 201- 400

e 401 - 621

iafee Olilano

Fig 7 NOx da ily moniloring track for March 9 2007 with winds from the NE

high values are located in the western end of the city close to the Niagara Escarpment as well as a long major streets which parallel the base of the escarpment (Fig 6) F ig 7 shows an example of a daily track for NOr on a single day March 9 2007 with winds from the northeast The impact of major highways particularly Hwy 403 with NO values ranging up to 621 ppb on this day is evident Traffic on major roads which feed into the main highshyways 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 experishyencing lower levels typically 50 ppb or less

The mobile data were oompared to concentrations recorded by a fixed cont inuous ambient air quality monitoring station located in lower Hamilton (4326deg N 7986deg V) This monitor is mainshytained by the MOE and the values represent average and maximum hourly data averaged over the period 2005- 2006 (Table I) The averaged MOE values are as expected lower than the instantaneous values gathered by the mobile monitoring unit The di fferences result in part from two factors First the MOE data represent averages for two years of continuous monitoring and include diurnal and seasonal variat ions while the mobile data represent averages of point concentrations recorded in the daytime o n weekdays These instan t in time data are subject to h igh variability as they a re affected by the moment-to-moment activi ty 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 act ivities The second facto r which influences the difference$ between the fi xed and mobile data relates t~ the

spatial coverage of each The MOE data reflect concentrations over limi ted spatial extent within the confines of the point locashyt ion of the monitor while the roaming mobile survey captures concentrations across the entire survey area The mobile data t herefore provide a more realistic perspective on population exposure as well as on pollution sources The high temporal density of the mobi le 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 a lso of the temporal variations from moment to moment

5 Conclusions

As with many indust rial cities in the world Hamilton has localized areas o f 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 wi thin 300 m is the zone of greatest health impact and it is therefore important to assess the pollution levels in these areas Mobile 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 wel l as uncertainties in meteoroshylogical 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 1t 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 networ k hourly maxima or averages F or example while a fixed monitor may record a maximum l h value of 250 ppb for NOx 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 bodys immediate reaction to such high bursts of pollution It is also of significance tl1a t a variety of pollutan ts are recorded as the toxic mix of many poll utants may he more consequential than expo shysure to any single pollutant as is sometimes the case in laborashytory 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 NOltgt 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 pa rticularly in congested traffic Concentrations in residential areas are relatively low averaging less t han 50 ppb NOx and

10 ppb S02 Both values are well below the I h ambient a ir quality criteria for N02 which is 200 ppb and for S02 which is 250 ppb4 However NOx 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 visib le 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 middot exposure of nearly a ll residents resu lt 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 Mobile 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 diITershycntial in source emissions such as regions with local ized indusshytries and a dispersed road networ k over a sprawled urban area

Acknowledgements

We would like to thank Clean Air Hamilton the City of Hamshyilton Ontario Ministry ofthe Environment and GeoConnections

middot for financial and in-kind support of this project

References

1 A Peters and C A Pope Ill Lancet 2002 360 1184-1 185 2 A J Cohen H R Anderson B Ost ra K D Pandey

M Krzyzanowski N Kiinzli K Gutschmidt A Pope J Romieu J M Samet and K Smith J Toxicol pound11vi011 Health Parr A 2005 68 1-7

3 Crileria Air Contaminam Emission Summaries Environment Canada 2007 httplwwwecgecapdbcac accessed Apr il 2008

4 Ontario M inistry of Environment Air Quali1y in Ontario 2006 Queens Printers for Ontario Toronto 2007

5 S Va rdoulak is N Gonzalez-Flesca B E A Fisher and K Pericleous Atmos Environ 2005 39 2725-2736

6 M Milton and A Steed E111bulliro11 Monit Assess 2007 124 1-19 7 Y Zhou and J I Levy BMC Public JiealtJ 2007 http

wwwbiomedcentralcom1471-2458789 accessed September 2008 8 U W Tang and z Wang J Air Waste Manage Assor 2006 56

1532-1539 9 R Atkinson A J Cohen J C Carrington and H R Anderson

Epidemiologv 2006 17(Suppl) Sl9 10 F Dominici R D Peng M L Bell L Pham A McDermott

S L Zeger and J M Samet JAMA J Am Med Assoc 2006 295 1127-1134

11 C A Pope III J B Muhlestein H T May D G Renlund J L Anderson and B D Horne Circulmio11 2006 114 2443-2448

12 X Xu J R Brook a nd Y Guo J Air WCste Manage Assoc 2007 57 1396-1406

13 X Yao N T Lau M Fang and C K Chan J Air Waste Ma11age Assoc 2006 56 144-151

14 V Isakov J S Touma and A Khlys tov J Air Waste Mmwge Assoc 2007 5 1286-1295

15 J Wa llace and P Kanaroglou Tra11sporratio11 Research Pltlrl D 2008 13 323- 333

16 Statistics Canada 2007 Community Profiles 2006 Census S tatistics Canada Catalogue no 92-591-XWE Ottawa httpwwwl2s tatcan cacensusmiddotrecensement2006dp-pdprof92-591 indexcfm accessed June 30 2008

17 ArcGIS version 9x Environmental Systems Research Inc (ESRJJ Redlands California 2008

J Environ Monit 2009 11 998- 1003 I 1003

spatial coverage of each The MOE data reflect concentrations over limi ted spatial extent within the confines of the point locashyt ion of the monitor while the roaming mobile survey captures concentrations across the entire survey area The mobile data t herefore provide a more realistic perspective on population exposure as well as on pollution sources The high temporal density of the mobi le 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 a lso of the temporal variations from moment to moment

5 Conclusions

As with many indust rial cities in the world Hamilton has localized areas o f 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 wi thin 300 m is the zone of greatest health impact and it is therefore important to assess the pollution levels in these areas Mobile 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 wel l as uncertainties in meteoroshylogical 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 1t 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 networ k hourly maxima or averages F or example while a fixed monitor may record a maximum l h value of 250 ppb for NOx 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 bodys immediate reaction to such high bursts of pollution It is also of significance tl1a t a variety of pollutan ts are recorded as the toxic mix of many poll utants may he more consequential than expo shysure to any single pollutant as is sometimes the case in laborashytory 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 NOltgt 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 pa rticularly in congested traffic Concentrations in residential areas are relatively low averaging less t han 50 ppb NOx and

10 ppb S02 Both values are well below the I h ambient a ir quality criteria for N02 which is 200 ppb and for S02 which is 250 ppb4 However NOx 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 visib le 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 middot exposure of nearly a ll residents resu lt 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 Mobile 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 diITershycntial in source emissions such as regions with local ized indusshytries and a dispersed road networ k over a sprawled urban area

Acknowledgements

We would like to thank Clean Air Hamilton the City of Hamshyilton Ontario Ministry ofthe Environment and GeoConnections

middot for financial and in-kind support of this project

References

1 A Peters and C A Pope Ill Lancet 2002 360 1184-1 185 2 A J Cohen H R Anderson B Ost ra K D Pandey

M Krzyzanowski N Kiinzli K Gutschmidt A Pope J Romieu J M Samet and K Smith J Toxicol pound11vi011 Health Parr A 2005 68 1-7

3 Crileria Air Contaminam Emission Summaries Environment Canada 2007 httplwwwecgecapdbcac accessed Apr il 2008

4 Ontario M inistry of Environment Air Quali1y in Ontario 2006 Queens Printers for Ontario Toronto 2007

5 S Va rdoulak is N Gonzalez-Flesca B E A Fisher and K Pericleous Atmos Environ 2005 39 2725-2736

6 M Milton and A Steed E111bulliro11 Monit Assess 2007 124 1-19 7 Y Zhou and J I Levy BMC Public JiealtJ 2007 http

wwwbiomedcentralcom1471-2458789 accessed September 2008 8 U W Tang and z Wang J Air Waste Manage Assor 2006 56

1532-1539 9 R Atkinson A J Cohen J C Carrington and H R Anderson

Epidemiologv 2006 17(Suppl) Sl9 10 F Dominici R D Peng M L Bell L Pham A McDermott

S L Zeger and J M Samet JAMA J Am Med Assoc 2006 295 1127-1134

11 C A Pope III J B Muhlestein H T May D G Renlund J L Anderson and B D Horne Circulmio11 2006 114 2443-2448

12 X Xu J R Brook a nd Y Guo J Air WCste Manage Assoc 2007 57 1396-1406

13 X Yao N T Lau M Fang and C K Chan J Air Waste Ma11age Assoc 2006 56 144-151

14 V Isakov J S Touma and A Khlys tov J Air Waste Mmwge Assoc 2007 5 1286-1295

15 J Wa llace and P Kanaroglou Tra11sporratio11 Research Pltlrl D 2008 13 323- 333

16 Statistics Canada 2007 Community Profiles 2006 Census S tatistics Canada Catalogue no 92-591-XWE Ottawa httpwwwl2s tatcan cacensusmiddotrecensement2006dp-pdprof92-591 indexcfm accessed June 30 2008

17 ArcGIS version 9x Environmental Systems Research Inc (ESRJJ Redlands California 2008

J Environ Monit 2009 11 998- 1003 I 1003