Overview

The goal of this project was to assemble information on inter- and intra- city traffic count data for the Greater Toronto Area, Windsor and Montreal. This meta-analysis will assess the availability and cost of data as well as the level of spatial and temporal disaggregation between cities. Ultimately, the data will lead to exposure estimates for zones within each of the three cities. To this end, two main sources were identified: collected traffic count data and modeled traffic count/emissions data.

SECTION A: TRAFFIC COUNT DATA

This section summarizes available traffic count data and includes contact information. It is divided into eight sub-sections: City of Toronto Roadways, City of Windsor Roadways, City of Montreal Roadways, Province of Ontario Roadways, Province of Quebec Roadways, the MCDS Company and a Summary of a Report on the Availability of Traffic Volume Commissioned by Environment Canada.

1a. City of Toronto

Source: City of Toronto Transportation Services (Traffic Data Centre & Safety Bureau)

Contact: Amy Deaves; 416-397-0857, adeaves@toronto.ca.
- When I sent a follow-up email, she referred any further questions to Jim Smith, Supervisor of Data Analysis; 416-392-5210, jim_smith@toronto.ca.
- Traffic Data Request Line: 416-392-8503 or 416-392-8643

A brochure (see attached documents) provided by the Traffic Data Centre gives a description of collected data. The data falls into two main categories, 24-hour vehicular volumes (automatic counts) and 8-hour manual volume counts. In general, the 24-hour counts involve a one-day sample obtained from road tubes. The exceptions are permanent count stations where traffic volume data is collected continuously every hour throughout the year (there are 122 such stations throughout Toronto). 24-hour volume counts are available for every major arterial road in the City of Toronto and are conducted every 2-3 years. The information can be found in 3 formats:

• 24 Hour Volume Map: a comprehensive map illustrating all roads and their vehicular volumes;
• Strip Plan: a schematic drawing showing 24 hour, AM peak hour, and PM peak hour volume of traffic flow passing along a particular section of roadway;
• Single Section/Intersection Summary: a detailed 24-hour traffic volume summary for a particular section/intersection.

For example:

Figure 1: Example of Traffic Data Available from the City of Toronto Traffic Data Centre

The manual traffic counts are obtained by counting the number of left turns, right turns, thru vehicles, bicycles, cars, trucks, buses and pedestrians crossing each approach. This raw data is obtained in 15-minute intervals during and 8-hour survey. The count is conducted during the following hours: 0730-0930, 1000-1200, 1300-1500, and 1600-1800. Data is available from 1985 to the present. At major signalized intersections, 8-hour surveys are conducted every 2-3 years. Minor signalized intersections are counted every 4-6 years. Approximately 900 intersection counts are taken each year. The centre also provides expansion factors. These are ratios used to normalize 8-hour intersection traffic volumes to average annual daily traffic (AADT) values. There are tables available for each of the various road classification types. The borders are Highway 427, Pickering, Lake Ontario and Steeles Ave. The Don Valley Parkway, Gardiner Expressway and Lakeshore Blvd. are included.

The Buckeridge paper summarizes the data they found for Toronto as follows: Twenty-four hour counts were directly available, or could be converted from 8-hour counts, for 104,1 km of the 219.0 km network. We converted eight-hour counts using a factor of 2.05. These data describe traffic on all major streets between 1990 and 1992 and secondary streets with traffic volume > 5,000 vehicles per day between 1987 and 1994. Traffic counts were georeferenced to digital Street Network File of Metro Toronto. We obtained data on vehicle type distribution throughout the study area from two sources. The first source was biennial manual counts of vehicle types performed by Metro Toronto Planning Department at 16 points in the study area. The average vehicle type distribution from this source over the years 1989, 1991, and 1993 provided an estimate of vehicle type distribution for 64.9% of modeled streets. We assigned the remaining 35.1% of streets the 1991 average vehicle type distribution in the Province of Ontario, obtained from the Ontario Ministry of Energy and the Environment."

1b.Transportation Tomorrow Surveys & Cordon Count Program

Source: Data Management Group, Joint Program in Transportation at the University of Toronto
35 St. George (Galbraith Bldg), Room 305

Phone (416) 978-7282
Fax (416) 978-3941
Contact: Susanna Choy, Phone (416) 978-3914, choystt@jpint.utoronto.ca

The Data Management Group in the Joint Program in Transportation maintains the data from two programs, the Transportation Tomorrow Survey (TTS) and the Cordon Count Program. TTS will be discussed later, in relation to EMME/2.

The Cordon Count is a periodic counting program involving over a thousand counting stations across the GTA. It was first performed in 1975 and the most recent data is for 2001. The count was last performed this year and the data should be available by late 2004/early 2005. The cordon count program represents a one-day snapshot of persons and vehicles passing each counting station. The counting stations are organized into screenlines, illustrated on the following map:

Figure 2: Locations of the Counting Stations Used in the Cordon Count Program

The counts are divided into 15-minute intervals and are stored by station. In many cases, traffic is counted manually, but automatic traffic records are also used. Vehicles are divided into the following classes: autos & taxis, light trucks, medium trucks, heavy trucks and buses. Summary reports are available in pdf form online while the detailed data can be accessed, free of charge, via an online database (to obtain access, fill out the request form, available online or on the attached CD, and either fax it to the office or deliver in person to Susanna Choy).

2. City of Windsor

Source: City of Windsor Infrastructure Planning

Contact: Wes Hicks, 519-255-6418, whicks@city.windsor.on.ca

The City of Windsor collects two types of traffic count data. AADT values are taken over 24-hour periods along arterials and collectors roadways. They are collected using road tubes – no distinction is made between vehicle types, however, as every two axels is calculated as one car, a large truck with sixteen wheels is seen as four cars. This data is available as a hard copy only. The city does have hourly counts as well, however, the contact said that it would be too onerous for them to provide us with this more detailed data. Sampling is done on a rotational basis, therefore, is location-dependant. The second data type is turning movement counts , taken at intersections only. They are performed every two to three years. These counts do differentiate between vehicles  and heavy vehicles  and are available electronically (either in excel or as a pdf). I asked what percentage of the city was surveyed, but he could not give me an estimate. Mr. Hicks is awaiting further contact from us with more details on the data required. Data is free for students, unless the amount of requested information is excessive. Also, digital counts would be free of charge.

3. City of Montreal

Contact: Mme. Lucy Gagne, 514-872-3130

I have not yet spoken with Mme. Gagne. Another City of Montreal employee referred her to me.

4. Ministry of Transportation, Ontario

i. Southwest Region

Contact: For general information, 519-873-4364

To request data, send a fax to Colleen Mayor (Traffic Characteristics Supervisor) at 519-873-4388.

The data is collected in 3-year cycles; thus, the most recent surveys should have

been gathered in 2001-2004. The information available is location-dependant; at

some points, counts are conducted manually and vehicle types are included. Loops are used on highways and road tubes on dirt roads and on-ramps. The data would be provided as a hard copy.

ii. Central Region

Contact: For general information, 416-235-5608 or call 416-235-5412 (switchboard)

To request data, send an email to Larry Smith (Manager) at larry.smith@mto.gov.on.ca outlining the project aims and information requested

The Central Region is bordered by Halton to the west, Durham to the east, Simcoe to the north and Niagara to the south. The data available includes the 400 series highways located within these boundaries. It is available in excel format and is free to students only. Counts are performed continuously, mainly with underground loops in the highways. Trend data is also available as well as vehicle types (to some extent).

iii. Eastern Region

Contact: For general information, 613-544-2220 (switchboard) or

Margaret Howes,

5. Transport Quebec, Ile de Montreal

Website: www1.mtq.gouv.qc.ca/fr/regions/montreal/circulation.asp

Contact: 514-873-7781 (General Information)

Traffic volume data for the highways on the Montreal Island are included in an online map. The data was collected in 2000 and represents an annual daily average of vehicles traveling in both directions. A portion of the map is included here:

Figure 3: Extract of the Map Illustrating AADT Values for Highways in the Montreal Area

This map can be accessed by going to the above website and clicking on the pdf link entitled Debit journalier moyen annuel . It is also included on the attached CD. In order to obtain data for roadways outside of the Montreal area, click on the link for the corresponding region.

6. MCDS (Marketing Communication Deployment Strategies)

Website: www.mcds.ca

Contacts:< Daniel Lemire, Vice-President of Sale
1425 boul. Rene Levesque Ouest, Montreal QC H3G 1T7
Phone (514) 397-4078 Ext. 244
Fax (514) 397-0425
Email: daniel.lemire@mcds.ca

The head office is in Montreal, but info for the Toronto office is:

412 Bedford Park Ave.
Toronto, ON
M5M 1K1
Phone (416) 785-5713

I called the Toronto office and was told that traffic count data was not among their products. I therefore suggest that any further communication be with their head office in Montreal.<

Audrey Smargiassi from the Montreal Department of Public Health provided the bulk of the following information. Her contact information is: asmargia@santepub-mtl.qc.ca, a website describing her work is: http://www.unites.uqam.ca/cinbiose/ANGLAIS/GENS/ASMARGIASSI.HTML.

MCDS provides a Canadian GDT traffic database that contains counts collected from various municipal, provincial and federal agencies from 1996 to 2003. The data is provided in MapInfo/ArchInfo, The price is to access Mapscape, which allows you to view one entry at a time (a database is not available from the Mapscape system). According to her previous discussions with MCDS, the Canadian file costs $15,000. The price for one province is $7,500, and any other geographic division (such as the Montreal island) costs $3,000. For example, the file contains about 2500 entries for Montreal.

I emailed M. Lemire with questions, but am still awaiting a reply. I will forward his email as soon as possible.

7. Summary of Relevant Points from ?Report to Environment Canada on Acquisition of Road Traffic Volume Data ? by Jacques Whitford Environment Limited (March, 2001)

- This report identified several sources of road traffic data:

1. Transport Canada has completed an ArcView GIS-based georeferenced database of Canada ?s primary highway network (approximately 90,000 km of road)
2. Provincial Ministries of Transportation, who are the primary source of information on vehicular movements across Canada ?s non-municipal primary and secondary roads (there are an estimated 160,000 km of secondary paved and unpaved roads); and
3. The majority of Canada ?s roads are owned and operated by municipalities (between 600,000 and 900,000 km of road).

- The authors suggest: In the event that the scope of work involved in collecting and converting provincial and municipal data is too exhaustive, other options may be available. For instance, it may be possible to determine air emissions from vehicles by using provincial figures on fuel sales tax revenues and use demographics data for the Census Metropolitan Areas to geographically distribute fuel consumption. Additionally, Natural Resources Canada has a database of registered vehicles by vehicle types, which is believed to be available for most urban centers.

- Transport Canada has produced a GIS map of Canada s principal highways with information with respect to AADT counts and rudimentary information with respect to vehicle types. In 2001, they were preparing a fully geo-referenced database of AADT counts for road segments of the primary road network under provincial control throughout Canada. This database contains 90,000 km of roads and includes roads under provincial control that reside within municipal boundaries, but no municipally controlled roads.

*Note: I tried to find somebody at Transport Canada that knew about the database mentioned in the report, however, was unsuccessful (I was directed from one person to the next without any results). The last contact was Lianna Belluz, out of the office until August 6^th, who should have contact info for the provincial transportation offices. Her number is 613-998-1943.

- The report includes summaries of the data available for Toronto, Windsor and Montreal. They are included here.

Figure 4a: Summary of Available Traffic Volume Data for Toronto, from the Whitford Report

Figure 4a: Summary of Available Traffic Volume Data for Montreal, from the Whitford Report

Figure 4a: Summary of Available Traffic Volume Data for Windsor, from the Whitford Report

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SECTION B: TRAFFIC MODELS

There are several disadvantages associated with using measured traffic count data. First, only major streets are sampled – Buckeridge et al.were able to find numbers for only 47.8% of the roadway network in the SETO. Second, there are no predictive capabilities. Third, there is both inter- and intra-city temporal variation. In consequence, a literature review was performed in order to determine whether traffic models would be more appropriate. The following section contains summaries of select studies as well as the contact information for relevant research groups.

1) Buckeridge DL, Glazier R, Harvey BJ, et al. 2002. Effect of motor vehicle emissions on respiratory health in an urban area. Environmental Health Perspectives, 110(3).

- They developed a refined exposure model and implemented it using a GIS to estimate the average daily census enumeration area (EA) exposure to PM<2.5 microns.

- Geographic data operations performed with ARC/INFO software (version 7.1, Environmental Systems Research Institute, Redlands, CA)

- Traffic count data obtained from governments (for 47.8% of road distance). Only streets with a traffic volume > 5,000 vehicles/day.

- A number of epidemiologic studies have attempted to examine the relationship between exposure to motor vehicle emissions and respiratory health. As a proxy for exposure, studies tend to model either traffic volume on the nearest road or distance to the nearest road.

- They developed a single-pollutant exposure model that accounts for traffic emissions from all major streets and considers traffic volume, distance to residence, and vehicle type mix. They then implement this model with a GIS to examine the desired relationships.

- They used an ecologic study design with the census EA as the unit of analysis. Southeast Toronto encompasses 16 km² and was divided into 334 EAs.

- They calculated PM emission factors for each vehicle type using the PART5 emission model (http://www.epa.gov/otaq/part5.htm). They then used vehicle type distribution, vehicle type emission factors, and traffic volumes to calculate the average daily mass of PM emitted on each street segment.

- They divided each EA into polygons and used a formula to calculate exposure values for each EA (g/24hr).

- Good discussion on study limitations.

Referenced Articles of Interest:

- Buckeridge D, Godzyra P, Ferguson K, et al, (1998). A study of the relationship between vehicle emissions and respiratory health in an urban area. Geogr Environ Model 2; 17-36.

- Office of Mobile Sources. Highway Vehicle Particulate Modelling Software (PART5). Ann Arbor, MI: U.S. EPA, 1995.

- Rayfield D, Longhurst JWS, Conlan DE, Watson AFR, Hewison T, (1995). Procedures for the estimation of vehicle emissions in an urban environment. In: Urban Transport and the Environment for the 21^st Century. Southampton, UK: Computational Mechanics Publications; 207-214.

2) Miller EJ and Lee A, (2002). A Personal Use Vehicle Emissions Audit for the Greater Toronto Area. Submitted to the Toronto Atmospheric Fund.

- The purpose of this study was to develop a procedure for estimating 24-hour emissions levels from light-duty personal-use vehicles in the GTA for a typical weekday using currently available data and modeling methods.

- Tools: Transportation Tomorrow Survey, EMME/2 transportation network modeling system for the GTA and Edmonton Emissions Model  – adapted to GTA.

- The Transportation Tomorrow Survey (TTS) is a comprehensive travel survey conducted in the GTA once every five years (1986, 1991, 1996, and 2001). Interviews of a representative population are conducted in order to better understand urban travel trends. TTS is geographically balanced and validated for representativeness against Census data; performed in. *Problem: Only personal-use light duty vehicle weekday trips.

- EMME/2 (http://www.inro.com) is a commercial software system to model the GTA road and transit transportation networks. It can store, display and edit computer representations of road and transit networks. Given known origin-destination flows (from TTS), it finds the path(s) through the network which trips are most likely to take. Thus, it yields estimates of travel times, speeds, volumes and congestion levels for each link in the road network. In particular, total emissions per street/expressway segment by emission type during a particular time period can be estimated from link length, volume, capacity and average speed, if a suitable emissions model is available to be programmed into EMME/2 (via macro).

- The Edmonton Emissions Model can use the link-based attributes generated by the EMME/2 assignment model to estimate vehicle emissions (carbon dioxide, carbon monoxide, hydrocarbons, nitric oxides and fuel consumption) by emission type. It had to be recalibrated for GTA conditions. The authors considered (and rejected) several models for their study: MOBILE5c (US EPA), MOBILE6 (US EPA) and Comprehensive Modal Emissions Model.

- Procedure involved taking estimated emissions from the model and reading them back into EMME/2 for display and analysis purposes. Would be useful to then feed emissions into an air dispersion model (though this was not done).

Additional Information Concerning EMME/2:

I spoke with Susanna Choy, a researcher in the Data Management Group within the Joint Program in Transportation. From her I received the following information:

- A student would be able to use this model free of cost with approval from the DMG. Learning to use the model is time-intensive; tutorials are available on-line.

- The model is divided into 2000 zones selected by regional planners.

- The model maintained by the university is for the GTA only. According to her, it would be very difficult to add the data required for Montreal and Windsor – she referred me to Professor Miller in this regard.

- Only larger roads and intersections are modeled.

- Cordon Count data has been used to validate the output from EMME/2.

- Professor Miller has developed a model with predictive capabilities.

- I asked about compatible emissions/dispersion models, but this was not her area of expertise. Again, she suggested a discussion with Professor Miller.

Miller EJ, (2001). The GTA Travel Demand Modeling System Version 2.0 ,Volume 1: Model Overview.

- Based on four-stage modeling system. Modeled in EMME/2.

- A 1677 zone system (from the 1996 TTS) covering the GTA (including Durham, York, Peel, Halton and Hamilton-Wentworth). In addition, 26 external zones used to represent travel between the GTA and adjacent regions outside the GTA.

- Predictive capabilities but only for the morning peak period (i.e. no 24-hour data).

- Additional information included in Alice Lee s thesis.

- In a separate paper, found in the Growing Together: Prospects for Renewal in the Toronto Region , Professor Miller states that a new 24-hour model has been developed.

Miscellaneous Notes of Interest

- Nicolai et al. used average daily traffic counts performed by the city administration for all streets with an a priori estimated vehicle count of >4,000/day (for 1,840 streets out of 19,000). The study was performed in Munich, Germany, a city in which most street segments are small side streets and had no counts available. The authors state that this may have led to some misclassification of traffic exposure. Further uncertainty is added as pollutant exposure values at the homes, derived from a validated model, were used to estimate personal exposure rather than direct personal samplers. Thus, this approach will only yield an approximation of real exposure.

- MILUTE (http://www.milute.mcgill.ca). Principal Investigator is Murtaza Haider (murtaza.haider@mcgill.ca; www.regionomics.com) who did his doctorate with E. Miller at U of T. From the website: The primary objective of this research is to develop an integrated transportation-land use and emissions model for the Greater Montr!"al Area (GMA). MILUTE will capture the behaviour of individual decision-makers, who face a multitude of choices regarding modes, routes, trip destinations and the like. MILUTE will explore the linkages between land use, urban form, and travel behaviour by using Geographic Information Systems (GIS).  One student project is entitled Modeling Travel Behaviour-Traffic Assignment . The purpose of this project is to develop a digital representation of the Montreal CMA street network in order to run accurate traffic assignment simulations (an origin-destination based model similar to EMME/2). From the website: The following picture is a typical result of the traffic assignment model after 25 iterations. The area shown is central Montreal with the St. Lawrence River on the right side and the D!"carie and M!"tropolitain freeways visible on the left. The colours indicate the level of congestion based on the volume to capacity ratio and the bandwidths describe the number of vehicles using each link :

- MOBILE5/5c/6: MOBILE6 (http://www.epa.gov/otaq/m6.htm) is an emission factor model for predicting gram per mile emissions of hydrocarbons, carbon monoxide, nitrogen oxides, carbon dioxide, particulate matter, and toxics from cars, trucks, and motorcycles under various conditions. It s an update of MOBILE5 (http://www.epa.gov/otaq/m5.htm). MOBILE5c is a modified version of MOBILE5a reflecting the base emission rate and deterioration rate of Canadian vehicles. For some information see Great Lakes Commission website: http://www.glc.org/air/scope/scope006.htm.

- There does not seem to be a group in the University of Windsor s Department of Civil and Environmental Engineering that conducts transportation research, however, their website includes a posting looking for an associate professor in this field. Perhaps, this is a subject that they will begin to investigate: The new faculty member is also expected to develop externally funded research projects, which will attempt to solve some of the crucial problems related to Canada-US international border crossing traffic as well as other transportation issues in Ontario. The research areas of particular interest include traffic engineering, transportation safety, economic analysis and resource allocation in transportation projects and programs, innovative technologies in transportation, like GIS and GPS.

Recommendations

It is my recommendation that traffic count data be used to calculate vehicle emissions for this project. The principal problem with modeled data lies with inconsistency between cities; while data would be readily available from the Data Management Group for the GTA, the same does not hold true for Montreal or Windsor. Similarly, for an inter-city comparison to be valid, the same model would have to be used for all three localities, work that is not available at this time. Additional concerns with modeled data include the substantial training time as well as the considerable assumptions imbedded in a program such as EMME/2 (i.e. why use estimations if measured data is available?).

There are, however, different problems associated with using the traffic count data available from the city. Primarily, the study will have no predictive capabilities. Also, data is only available for major roadways (though this is also the case with EMME/2). Buckeridge et al. found data for 47.8% of the SETO network that describes traffic on all major streets and secondary streets with traffic volume > 5,000. Another concern is inter- and intra-city temporal disaggregation; within the data set, sampling occurred approximately over a four-year period (each city operates on a different schedule and takes measurements of a percentage of their network each year). For both issues, sensitivity analyses could be performed to determine the effect of each limitation. Contrastingly, compensatory techniques could be used – for example, traffic volumes could be assigned to small roadways or older data could be multiplied by a factor to make it more current.

According to Professor Diamond, no emission models exist for PAHs. Thus, the amount of vehicle kilometers traveled within each block  will be multiplied by an emission factor in a formula similar to the following:

where:

is the average emission rate for link i in mg/day

is the link length in km

is the number of vehicles per day

is the emission factor in mg/km

(Source: Alison Bodurtha)

Consequently, additional information such as road surface type, vehicle speed, ambient temperature as well as cold start or evaporative emissions are not required.

In terms of procedure, I suggest that the Buckeridge et al. paper be used as a starting point. The authors divided their region of interest using census enumeration areas. Presumably, this will facilitate the integration of health and socio-economic data with the traffic counts. For traffic volumes, the city contacts listed above should be contacted and data obtained. This will yield a better idea on how comprehensive the data is, especially in regards to vehicle type information. Additionally, the decision can be made whether it is too time intensive to manually reference the vehicle counts to a road map. Traffic count data, already inputted into the Mapscape program is available for purchase from companies like MCDS. This is a costly option, especially since the Ministries of Transportation would be willing to provide the data free of charge.

The traffic counts will likely need to be supplemented by data from the province. Buckeridge et al. found that city data provided them with an estimate of vehicle type distribution for 64.9% of modeled streets. They assigned to the remaining 35.1% of streets the average vehicle type distribution in the Province of Ontario; they supposed that the impact of this assumption was minimal.

Bibliography

(The articles can be found either as a hard copy or in electronic form on the attached CD.)

1) Buckeridge DL, Glazier R, Harvey BJ, et al, (2002). Effect of motor vehicle emissions on respiratory health in an urban area. Environmental Health Perspectives, 110(3).

2) Bodurtha A, (2003). Modeling Emissions of Air Toxics from Mobile Sources in the GTA: Challenges and Prospects. Undergraduate Thesis, University of Toronto. (Hard Copy)

3) Angelino E, Bardeschi A, Colucci A, Gnagnetti M, Gualdi R, Meda M, Tamponi M, Tebaldi G, (1993). Planning model for the assessment of air pollution caused by urban traffic. The Science of the Total Environment, 134; 9-19. (Hard Copy)

4) Miller EJ, (2001). The GTA Travel Demand Modeling System Version 2.0 ,Volume 1: Model Overview. (Hard Copy)

5) Jacques Whitford Environment Limited, (2001). Report to Environment Canada on Acquisition of Road Traffic Volume Data. (Hard Copy)

6) Miller EJ and Lee A, (2002). A Personal Use Vehicle Emissions Audit for the Greater Toronto Area. Submitted to the Toronto Atmospheric Fund. (Hard Copy)

7) INRO Consultants Inc. EMME/2 Transportation Planning System Brochure. (Hard Copy)

8) Sturm PJ, Pucher K, Sudy C, Almbauer RA. Determination of traffic emissions – intercomparison of different calculation methods. The Science of the Total Environment, 189/190; 187-196. (Hard Copy)

9) Nicolai T, Carr D, Weiland SK, Duhme H, von Ehrenstein O, Wagner C, von Mutius E. (2003) Urban traffic and pollutant exposure related to respiratory outcomes and atopy in a large sample of children. Eur Respir J, 21: 956-963. (Hard Copy)

10) Namdeo AK, Colls JJ. Development and evaluation of SBLINE, a suite of models for the prediction of pollution concentrations from vehicles in urban areas. (1996) The Science of the Total Environment, 189/190; 311-320. (Hard Copy)

11) Bachman W, Sarasua W, Hallmark S, Guensler R. Modeling regional mobile source emissions in a GIS framework. (2000). Transportation Research Part C (8); 205-229. (Hard Copy)

12) Mensink C, De Vlieger I, Nys J, (2000). An urban transport emission model for the Antwerp area. Atmospheric Environment, 34; 4595-4602. (Hard Copy)

13) Lindley SJ, Conlan DE, Raper DW, Watson AFR, (1999). Estimation of spatially resolved road transport emissions for air quality management applications in the North West region of England. The Science of the Total Environment, 235; 119-132. (Hard Copy)

14) Traffic Data Centre and Safety Bureau. Traffic Data Catalogue. (Hard Copy)

15) Transport Quebec. Debit journalier moyen annuel. (Electronic Copy)

16) Data Management Group. Cordon Count Retrieval Request Form. (Electronic Copy)

17) Corridor Management Office – MTO Central Region. Map with Highway Classifications. (Electronic Copy)

18) City of Toronto Urban Development Services. 1998 Cordon Count Brochure. (Electronic Copy)

19) Miller EJ, Shalaby A, (2003). Evolution of Personal Travel in Toronto Area and Policy Implications. J. Urban Planning & Development, 129(1); 1-26. (Electronic Copy)

20) Data Management Group, (2003). 2001 GTA Cordon Count, Transportation Trends 1991-2001-Executive Summary. (Electronic Copy)

21) Data Management Group, (2003). 2001 GTA Cordon Count, Transportation Trends 1991-2001-Technical Report. (Electronic Copy)

22) Data Management Group, (2003). 2001 GTA Cordon Count, Transportation Trends 1991-2001-Appendices A&B. (Electronic Copies)

23) Miller EJ, (2002). Articles in Growing Together: Prospects for Renewal in Toronto Region, Background Reports. (Electronic Copy)

24) US EPA, (1993). Mobile5 Information Sheet #2: Estimating Idle Emission Factors Using Mobile 5. (Electronic Copy)

25) Statistics Canada. Toronto Census Tracts, 2001 Population Density. Prepared by Brock University Map Library. (Electronic Copy