Kitchener Corridor Air Quality Study Report

GO Rail Network Electrification Project Final Environmental Project Report Addendum

APPENDIX F3: Kitchener Corridor Air Quality Study Report

Local Air Quality Study – Kitchener Corridor

GO Rail Network Electrification Project

03-Dec-2020

Prepared by:

Contract: QBS-2017-CKU-001 Revision DE

Authorization

X X Alain Carriere Amber Saltarelli Senior Project Manager Project Manager

X Andy Gillespie Program Manager

REVISION HISTORY

Revision Date Purpose of Submittal Comments

DA 17-Jul-2019 Draft submission to Metrolinx N/A

DB 08-Sep-2020 Revision addressing Metrolinx comments N/A

DC 05-Oct-2020 Revision addressing Metrolinx comments N/A

DD 09-Oct-2020 Revision addressing Metrolinx comments N/A

DE 03-Dec-2020 Revised Submission N/A

This submission was completed and reviewed in accordance with the Quality Assurance Process for this project.

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Executive Summary

Metrolinx and Hydro One (as co-proponents) jointly completed the GO Rail Network Electrification Transit Project Assessment Process (TPAP) in 2017 to convert six Metrolinx-owned Rail Corridors from diesel to electric propulsion. Once electrification is implemented, the system will operate with a mixed fleet of diesel and electric trains, as not all tracks on all corridors will be electrified. Metrolinx currently has a fleet of 91 diesel locomotives, of which 17 are relatively new or recently refurbished models that comply with the most stringent emission limits (Tier 4), while the remainder cover a range of ages and emission levels (Tier 0 to Tier 3). Since 2017, Metrolinx has developed a more detailed design and schedule for how increased passenger service will be delivered for the GO Rail Expansion Program in the future, involving further infrastructure and rail traffic changes. These proposed changes require a reassessment of potential air quality impacts as part of an addendum to the 2017 Electrification EPR. Local air quality impacts along the Rail Corridors are related to the continued use of diesel locomotives after electrification is complete. In addition, temporary impacts will be associated with construction activities supporting the implementation of the expansion program. RWDI was retained to complete a local air quality impact assessment for the GO Rail Network to support the addendum to the 2017 Electrification EPR. The objective of this study was to assess air quality effects and how they will change from existing operations (2015) to the proposed future operations. The projected future rail service levels are based on a horizon year of 2037 and include an added 10% safety factor. This report addresses potential local air quality impacts from future operations along the Kitchener (KT) Rail Corridor, west of the UP Express Pearson International Airport Spur at Highway 427. The portion of the KT Rail Corridor east of the UP Express Spur has been assessed as part of the Addendum to the 2014 UP Express Electrification TPAP. Other Corridors are addressed in separate Air Quality Study reports. Likewise, regional air quality effects, temporary air quality impacts during construction, and greenhouse gas emissions are addressed elsewhere. The scope, approach and work plan for air quality studies for Metrolinx rail infrastructure projects as part of a TPAP follow guidance provided in the “ON Corridor Air Quality and Greenhouse Gas Emissions Study” (DRAFT #3, September 5, 2019) (Air Quality Work Plan). Computer dispersion modelling was used to predict concentrations of key air contaminants at representative receptors in proximity to the rail corridor. The modelled sections of the Kitchener Corridor includes an 800 m section just east of Malton GO Station. These are the sections that have residential and other sensitive uses in proximity to the rail corridor. The remainder of the study area has no residential areas near the tracks. Concentrations of relevant air contaminants were predicted under worst-case meteorological conditions and reasonably worst-case background air quality conditions. This was done for numerous receptor locations, so that the worst-case receptor location(s) could be identified. The results for the worst-case receptor locations indicated the following:

• PM2.5, PM10, Acrolein, Carbon Monoxide, Formaldehyde, Acetaldehyde, and 1,3-Butadiene are all predicted to be within the provincial air quality criteria (AAQCs) in both the Baseline and Future Scenario.

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• 24-hour Benzene meets the AAQC in both scenarios, but the annual average Benzene does not in either scenario. The AAQCs and CAAQS represent desirable levels, rather than statutory limits. Measures mandated to achieve the CAAQS should consider technical achievability, practicality and implementation costs (CCME, 2019).

Further examination of the model results for NO2 showed that the cumulative concentrations decline sharply within the first 150 m from the rail corridor. The predicted future daily maximum 1-hour NO2 levels (98th percentile) fall within the 2020 CAAQS objective at approximately 50 m from the rail corridor, and within the 2025 CAAQS objective at approximately 100 m from the rail corridor. The predicted future annual average concentrations remain above the 2020 and 2025 CAAQS objective at all distances within the study area. This is because the background level of annual NO2 used in the analysis is above the 2025 CAAQS objective.

A detailed examination of predicted cumulative NO2 concentrations at 10 representative receptors showed that the maximum hourly concentrations increase by 14% to 62% between the Baseline and Future Scenario, but the mean and median concentrations change by less than 10%, except at ground- level locations immediately adjacent to worst-case areas of the corridor (Receptors 1, 2, 9, and 10). The predicted hourly concentrations in the Future Scenario are below the 2020 CAAQS level just below 99% of the time at Receptors 2 and 9, which are adjacent to the rail corridor, and 100% of the time at all the other representative receptors. They are below the 2025 CAAQS level approximately 96% to 99% of the time at Receptors 1, 2, 9, and 10, and 100% of the time at all other representative receptors

The average cumulative NO2 concentrations at the representative receptors are dominated by the background contribution, except Receptor 1 in the Future Scenario, where the cumulative concentration is dominated by the rail corridor. The average contribution of Metrolinx-related emission sources is higher in the Future Scenario than in the Baseline Scenario but remains small compared to background (approximately 14% or less), except at Receptors 1, 2, 9, and 10, which are adjacent to the corridor. Further examination of the model results for Benzene and Benzo(a)pyrene showed that the predicted contribution of Metrolinx-related sources to the cumulative concentrations is very small (generally less than 10%). Separate Assessment of Construction and Operation Phase Impacts on Local Air Quality Due to the exceptional size and complexity of the GO Expansion program, Metrolinx assessed the Air Quality impacts of the construction and operation phases of the Project in individual separate reports. The construction phase reports deal only with the construction phase of the individual infrastructure component (ex. grade separation, bridge improvement, pedestrian tunnel) at a given location and are written independently by experts. The operation phase reports deal with the air quality impacts of the daily operation of trains on each expanded and improved rail corridor, which is part of the GO Expansion program. The construction phase local air quality impacts of new layover facilities are included in the operation phase reports. These provisions are described in the Metrolinx work plan for the Air Quality study of the GO Expansion program, which was submitted to MECP prior to the commencement of the study. The operation phase reports address the air quality impacts of train operations per planned “maximum” service levels on the expanded and improved rail network - fully accounting for every relevant element of the infrastructure – including the new grade separations, new/improved bridges, and layover facilities. Hence, the rail noise and vibration implications of the proposed infrastructure are accounted for in the operation phase reports of each corridor, rather than in individual construction phase reports. This provides for a more consistent and efficient assessment process.

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The potential air quality impacts of any change in road traffic conditions resulting from grade separation and other component projects are not assessed, since these are expected to be insignificant and generally positive (a reduction in air contaminant emissions). In addition to local air quality impacts, Metrolinx assessed also the system-wide, regional air contaminant and greenhouse gas emission implications of the OnCorr Project in a separate, stands-alone report. This report quantifies the direct cumulative net effect of the GO Expansion program on the regional inventory of air contaminant and greenhouse gas emissions.

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Table of Contents

Executive Summary ...... i Documents...... vii Glossary of Terms ...... ix Abbreviations ...... xi 1 Introduction ...... 1 1.1 Project Scope ...... 2 1.2 Project Assessment Approach ...... 4 2 Study Description ...... 5 2.1 Air Quality Study Area ...... 5 2.2 Train Schedule ...... 7 3 Local Air Quality Assessment ...... 8 3.1 Air Contaminants and Thresholds ...... 8 3.2 Background Air Quality ...... 9 3.3 Receptors ...... 11 3.4 Sources of Emissions ...... 14 3.5 Model Selection ...... 14 3.5.1 Terrain Data ...... 14 3.5.2 Meteorological Data ...... 14 3.5.3 Chemical Transformation of Nitrogen Oxides ...... 14 3.6 Rail Activity Modelling ...... 15 3.6.1 Emission Factors ...... 15 3.6.2 Emission Calculation ...... 16 3.6.2.1 Moving Trains ...... 17 4 Modelling Results ...... 19

4.3 Nitrogen Dioxide (NO2) ...... 24 4.4 Benzene and Benzo(a)Pyrene ...... 31 5 Conclusion ...... 34

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Tables

TABLE 1: AIR QUALITY OBJECTIVES TABLE 2: SUMMARY OF BACKGROUND CONCENTRATION LEVELS IN STUDY AREA

TH TABLE 3: 90 PERCENTILE BACKGROUND NO2 AND PM2.5 CONCENTRATIONS BY HOUR OF DAY

TH TABLE 4: 90 PERCENTILE VARYING HOURLY BACKGROUND CONCENTRATIONS FOR O3

TABLE 5: SPECIATION FACTORS FOR PM2.5, PAHs, VOCs, AND CARBONYLS TABLE 6: TIER-WEIGHTED EMISSION FACTORS TABLE 7: NOTCH SETTING AND CORRESPONDING BRAKE HORSEPOWER FOR MP-40 LOCOMOTIVE TABLE 8: AVERAGE GO TRAIN SPEED AND HORSEPOWER ASSUMPTIONS FOR STUDY AREA TABLE 9: MAXIMUM MODELLED CONCENTRATIONS FOR BASELINE (2015) SCENARIO TABLE 10: MAXIMUM MODELLED CONCENTRATIONS FOR FUTURE (TSS1) SCENARIO TABLE 11: SELECTED REPRESENTATIVE RECEPTOR LOCATIONS

TABLE 12: RANGE OF PREDICTED CUMULATIVE 1-HOUR NO2 AT SELECTED RECEPTORS

TABLE 13: SOURCE CONTRIBUTIONS TO AVERAGE NO2 AT SELECTED RECEPTORS TABLE 14: SOURCE CONTRIBUTIONS TO AVERAGE BENZENE AT SELECTED RECEPTORS TABLE 15: SOURCE CONTRIBUTIONS TO AVERAGE BENZO(A)PYRENE AT SELECTED RECEPTORS TABLE 16: SUMMARY OF POTENTIAL EFFECTS, MITIGATION MEASURES AND MONITORING – AIR QUALITY

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Figures

FIGURE 1: CURRENT METROLINX CORRIDORS FIGURE 2: KITCHENER AIR QUALITY STUDY AREA FIGURE 3: RECEPTOR LOCATIONS IN THE KITCHENER AIR QUALITY STUDY AREA FIGURE 4: LOCATIONS OF WORST-CASE RECEPTORS IN BASELINE SCENARIO FIGURE 5: LCOATIONS OF WORST-CASE RECEPTORS IN FUTURE SCENARIO

FIGURE 6: FUTURE MAXIMUM ANNUAL NO2 IN STUDY AREA

TH FIGURE 7: FUTURE MAXIMUM 98 PERCENTILE DAILY MAXIMUM 1-HOUR NO2 IN STUDY AREA FIGURE 8: LOCATIONS OF REPRESENTATIVE RECEPTORS

Appendices

APPENDIX A: TSS1 SCHEDULE FOR KIT CORRIDOR APPENDIX B: BACKGROUND AIR QUALITY CONCENTRATIONS IN STUDY AREA APPENDIX C: BASELINE (2015) AND FUTURE (TSS1) HOURLY RAIL SERVICE LEVELS IN KIT CORRIDOR APPENDIX D: SAMPLE CALCULATION AND ADDITIONAL DETAILS OF EMISSION RATES FOR LOCAL AIR QUALITY ASSESSMENT APPENDIX E: EMISSION SOURCE ORIENTATION IN AERMOD

APPENDIX F: FREQUENCY CURVES FOR HOURLY NO2

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Documents

Title Reference

Metrolinx: GO Rail Network Electrification EPR, 2017 http://www.metrolinx.com/en/electrification/electric.aspx http://www.metrolinx.com/en/docs/pdf/board_agenda/20 GO Expansion Full Business Case, Metrolinx (November 2018) 181206/20181206_BoardMtg_GO_Expansion_Full_Busi ness_Case.PDF ON Corridor Air Quality and Greenhouse Gas Emissions Study” n/a (DRAFT #3 (September 5, 2019) Ministry of Transportation Environmental Guide for Assessing and Mitigating the Air Quality Impacts and Greenhouse Gas https://ero.ontario.ca/notice/019-0131 Emissions of Provincial Transportation Project (October 2019) PM Hot-spot Analyses: Guidance (US EPA-420-B-15-084, https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100NM November 2015) XM.pdf Air Quality in Ontario Reports, 2013 – 2017 http://www.airqualityontario.com/press/publications.php http://data.ec.gc.ca/data/air/monitor/national-air- National Air Pollutant Survey data, 2013-2017 pollution-surveillance-naps-program/Data- Donnees/?lang=en “Control of Emissions of Air Pollution from Locomotive Engines https://www.govinfo.gov/content/pkg/FR-2008-06- and Marine Compression-Ignition Engines Less Than 30 Litres 30/pdf/R8-7999.pdf per Cylinder" 73 Federal Register 126 (30 June 2008) “Emission Factors for Locomotives”, US EPA Office of https://nepis.epa.gov/Exe/ZyPDF.cgi/P100500B.PDF?D Transportation and Air Quality (April 2009) ockey=P100500B.PDF “Control of Emissions of Air Pollution from Nonroad Diesel https://www.govinfo.gov/content/pkg/FR-1998-10- Engines”, US EPA (23 October 1998) 23/pdf/98-24836.pdf “Control of Emissions of Air Pollution from Nonroad Diesel https://www.govinfo.gov/content/pkg/FR-2004-06- Engines and Fuel”, US EPA (29 June 2004) 29/pdf/04-11293.pdf “Control of Emissions of Air Pollution from Locomotives Engines https://www.govinfo.gov/content/pkg/FR-2008-06- and Marine Compression-Ignition Engines Less Than 30 Litres 30/pdf/R8-7999.pdf per Cylinder”, US EPA (30 June 2008) “Speciation Profiles and Toxin Emission Factors for Nonroad https://nepis.epa.gov/Exe/ZyPDF.cgi/P100UXK7.PDF?D Engines in MOVES2014b”, US EPA (July 2018) ockey=P100UXK7.PDF C27 Generator Set Electric Power Specifications Sheet n/a

TSS1 Train Service Schedule, Metrolinx (April 2020) n/a

“Estimation of historical annual PM2.5 exposures for health effects https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseactio assessment”, Lall et al. (14 Jan 2004) n/display.files/fileID/13226 Ontario’s Ambient Air Quality Criteria, Ontario Ministry of https://www.ontario.ca/page/ontarios-ambient-air- Environment, Conservation, and Parks (2016) quality-criteria-sorted-contaminant-name Canadian Ambient Air Quality Standards, Canadian Environmental Protection Act, Federal Government of Canada http://airquality-qualitedelair.ccme.ca/en/ (May 2013) “Guidance Document on Air Zone Management”, Canadian https://www.ccme.ca/files/Resources/air/Guidance%20D Council of Ministers of the Environment (CCME, 2019) ocument%20on%20Air%20Zone%20Management.pdf O. Reg. 419/05: Air Pollution – Local Air Quality https://www.ontario.ca/laws/regulation/050419 Air Quality in Ontario 2017 Report, Ontario Ministry of https://www.ontario.ca/document/air-quality-ontario- Environment, Conservation and Parks (MECP, 2017) 2017-report Map: Regional Meteorological and Terrain Data for Air https://www.ontario.ca/environment-and-energy/map- Dispersion Modelling, Ontario Ministry of Environment, regional-meteorological-and-terrain-data-air-dispersion- Conservation, and Parks (Jan 2020) modelling

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Title Reference https://www.gotransit.com/en/trip- Full Schedules, Trip Planning, GO Transit planning/seeschedules/full-schedules https://www.toronto.ca/legdocs/bylaws/2010/law0775.pd City of Toronto, BY-LAW No. 775-2010 f

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Glossary of Terms

Word Definition A steady-state plume model that incorporates air dispersion based on planetary AERMOD boundary layer turbulence structure and scaling concepts. Brake horsepower The available power of an engine. A railroad car is a vehicle used for the carrying of cargo or passengers on a rail Car transport system. Future rail service levels, schedules and technologies expected to capture “Credible worst-case scenario” worst-case effects from sound and vibration; the basis for the EA amendment. Contaminants usually associated with rail/road emissions and for which there are Criteria Air Contaminant clear criteria established provincially or federally. The composition of a train, including type and number of locomotives and Consist number of cars. Carbon Monoxide A colourless and odourless gas and a by-product of combustion. The chemical process where a substance reacts with oxygen to release Combustion energy. A value that relates the quantity of a pollutant released to the atmosphere with an Emission Factors activity associated with the release of that pollutant. A means of controlling an engine's power by regulating the amount of fuel or air Engine Throttle entering the engine. A group of combustible materials that have been formed from decayed plants and Fossil Fuels animals. These materials are often used as fuel by combusting them to release energy. Fossil fuels include oil, coal, and natural gas. Freight Trains Trains that transport cargo instead of passengers Greenhouse Gases Gases that trap heat in the atmosphere The electrical power distribution system that provides lighting and HEP Unit heating/cooling. A number of adjacent volume sources that follow a given line path (such as a Line Volume Source railway track). Each segment of a line volume source acts as an individual volume source Locomotive Rail transport vehicle that provides the motive power for a train A megawatt is a unit for measuring power that is equivalent to one million watts of Megawatt-hour electricity used continuously for an hour A group of gaseous substances that are by-products of combustion, including Nitrogen Oxides nitrogen oxide (NO) and nitrogen dioxide (NO2). GO and VIA train movements that do not carry passengers. These movements Non-Revenue Trains typically occur between layovers or maintenance facilities and GO Stations. Notch Setting Each of the throttle control positions on a locomotive engine are called a notch.

A technique for estimating NO2 concentrations based on the NOX and Ozone Ozone Limiting Method concentrations. Microscopic solid or liquid particles that can become airborne. Particulate matter Particulate Matter can be inhalable (PM10) and/or respirable (PM2.5). Point Source A single identifiable source of emissions, such as an exhaust stack The scenario following the implementation of the future infrastructure and rail Post-project operations. The baseline scenario of rail operations. In this study, the baseline scenario is the Pre-project year 2015. The main legislation that gives Transport Canada responsibility for overseeing rail Railway Safety Act safety

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Word Definition

Receptor A location that has the potential to be adversely affected by a contaminant GO or VIA train movements that carry passengers between Stations. These trains Revenue Trains do not stop at layovers or maintenance facilities. VIA Rail Trains Passenger trains that travel through portions of the Metrolinx Corridors Organic chemicals with a high vapour pressure at room temperature, which allows Volatile Organic Compounds them to enter the surrounding air Volume Source A volume source of emissions is a three-dimensional source of pollution

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Abbreviations

Acronym or Abbreviation Definition AAQC Ambient Air Quality Criteria

AQMP Air Quality Management Plan

AERMOD Air Quality Dispersion Modeling – the US EPA’s preferred dispersion model

APTA American Public Transportation Association

AREMA American Railway Engineering and Maintenance of Way Association

B(a)P Benzo(a)pyrene

Bhp Brake horsepower

CAAQS Canadian Ambient Air Quality Standards

CAC Criteria Air Contaminant

CO Carbon Monoxide

CN Canadian National Railway

CP Canadian Pacific Railway

EA Environmental Assessment

EPR Environmental Project Report

EU European Union

G Grams

GHG Greenhouse Gas

HC Hydrocarbon

HEP Head End Power

Hr Hour

MECP Ontario Ministry of Environment, Conservation and Parks

MTO Ontario Ministry of Transportation

NAAQS National Ambient Air Quality Standards

NAPS National Air Pollution Surveillance

NO Nitric Oxide

NO2 Nitrogen Dioxide

NOX Nitrogen Oxides

OLM Ozone Limiting Method

PM2.5 Particulate Matter with a diameter of 2.5 micrometers or less

PM10 Particulate Matter with a diameter of 10 micrometers or less

Ppb Parts per Billion

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Acronym or Abbreviation Definition TSS1 Train Service Schedule (version for credible worst-case scenario)

US EPA United States Environmental Protection Agency

VOC Volatile Organic Compound

WHO World Health Organization

µg/m3 Micrograms per Metre Cube

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1 Introduction

Metrolinx and Hydro One (as co-proponents) jointly completed the GO Rail Network Electrification Transit Project Assessment Process (TPAP) in 2017 to convert Metrolinx-owned Rail Corridors from diesel to electric propulsion. The 2017 Environmental Project Report (EPR) assessed the environmental effects associated with: • the increase in rail traffic associated with the conversion from diesel to electric propulsion; • infrastructure improvements; and • installation of proposed traction power supply and power distribution components. The TPAP received a Notice to Proceed and Metrolinx issued a Statement of Completion in December 2017. Since December 2017, Metrolinx developed a reference concept design that details how increased passenger service will be delivered for the GO Rail Expansion Program in the future. This work led to further proposed changes to rail infrastructure and a revised future train service schedule, referred to as TSS1 (presented in Appendix A), including descriptions of train type, (diesel locomotive, electric locomotive), and train consists. As a result of these proposed changes the 2017 Electrification EPR must be amended. Existing and future air quality impacts associated with these changes were predicted to assess potential effects in accordance with the applicable guidelines. Separate Assessment of Construction and Operation Phase Impacts on Local Air Quality Due to the exceptional size and complexity of the GO Expansion program, Metrolinx assessed the Air Quality impacts of the construction and operation phases of the Project in individual separate reports. The construction phase reports deal only with the construction phase of the individual infrastructure component (ex. grade separation, bridge improvement, pedestrian tunnel) at a given location and are written independently by experts. The operation phase reports deal with the air quality impacts of the daily operation of trains on each expanded and improved rail corridor, which is part of the GO Expansion program. The construction phase local air quality impacts of new layover facilities are included in the operation phase reports. These provisions are described in the Metrolinx work plan for the Air Quality study of the GO Expansion program, which was submitted to MECP prior to the commencement of the study. The operation phase reports address the air quality impacts of train operations per planned “maximum” service levels on the expanded and improved rail network - fully accounting for every relevant element of the infrastructure – including the new grade separations, new/improved bridges, and layover facilities. Hence, the rail noise and vibration implications of the proposed infrastructure are accounted for in the operation phase reports of each corridor, rather than in individual construction phase reports. This provides for a more consistent and efficient assessment process. The potential air quality impacts of any change in road traffic conditions resulting from grade separation and other component projects are not assessed, since these are expected to be insignificant and generally positive (a reduction in air contaminant emissions). In addition to local air quality impacts, Metrolinx assessed also the system-wide, regional air contaminant and greenhouse gas emission implications of the OnCorr Project in a separate, stands-alone report. This report quantifies the direct cumulative net effect of the GO Expansion program on the regional inventory of air contaminant and greenhouse gas emissions.

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1.1 Project Scope The air quality analysis addresses changes to rail infrastructure and the new TSS1 train service schedules. The TSS1 train service schedules include descriptions of train type (diesel locomotive, electric locomotive) and train consists. The scope includes seven Metrolinx-owned Rail Corridors: • Union Station • Lakeshore West (including the Canpa Subdivision) • Kitchener (up to the Halton Subdivision) • Barrie • Stouffville • Lakeshore East • Richmond Hill [up to Mile 4.38 (Pottery Road)] Although not within the scope of the study, all traffic associated with the Milton Corridor is considered within RWDI’s study where appropriate (e.g., where these trains enter into or leave Union Station). All current Metrolinx Corridors are shown in Figure 1.

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FIGURE 1: CURRENT METROLINX CORRIDORS

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1.2 Project Assessment Approach Metrolinx developed a draft internal document entitled, “ON Corridor Air Quality and Greenhouse Gas Emissions Study” (DRAFT #3, September 5, 2019) (Air Quality Work Plan), which describes in detail the scope and approach followed for the current work. Where appropriate, details of the assessment took into consideration elements of methodologies outlined in the following guidelines: • Ministry of Transportation Environmental Guide for Assessing and Mitigating the Air Quality Impacts and Greenhouse Gas Emissions of Provincial Transportation Project (October 2019); and • PM Hot-spot Analyses: Guidance (US EPA-420-B-15-084, November 2015). Metrolinx provided pertinent information, such as baseline and future train volumes, trip log data including throttle and speed profiles, and track diagrams, for incorporation within this assessment. Where information was not available, assumptions were documented for approval by Metrolinx. To assess air quality effects of diesel locomotive emissions, the methodology involved a computer simulation technique known as dispersion modelling, which consists of estimating emissions associated with the rail corridor and predicting worst-case concentrations of key air contaminants at representative receptors in proximity to the rail corridor. This was done for both a baseline scenario (2015) and a future scenario with proposed infrastructure and service level changes in place. The TSS1 future rail service schedule used in this study was based on a projection to 2037, with a 10% added safety factor. This report addresses potential local air quality impacts from future operations along the Kitchener (KT) Rail Corridor, west of the UP Express Pearson International Airport Spur at Highway 427. Other Corridors are addressed in separate Air Quality Study reports. Likewise, regional air quality effects, temporary air quality impacts during construction, and greenhouse gas emissions are addressed elsewhere.

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2 Study Description

2.1 Air Quality Study Area The local air quality study focused on sections of the Kitchener Corridor (west of the UP Express Pearson International Airport Spur) where sensitive receptors are located close enough to the tracks to potentially experience air contaminant levels that are significantly above background levels. Sections of the corridor that had significant numbers of residences and other sensitive receptors within 150m of the tracks were modelled, and sections that were dominated by industrial or commercial uses within 150m of the tracks were not modelled. The study area segment begins east of Malton GO station, at Airport Road, and continues approximately 800 m to the west. The area studied along this segment extended to a distance of 300 m away from the tracks. The Kitchener Corridor study area is shown in Figure 2. There are no GO Train stations within the modelled study area.

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FIGURE 2: KITCHENER AIR QUALITY STUDY AREA

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2.2 Train Schedule For the EPR addendum, the Pre-project (baseline) year is 2015. The Post-project (future) scenario is based on implementation of the improvements together with future GO Transit train traffic as detailed in the TSS1 rail schedule provided by Metrolinx. Baseline service levels are based on the maximum levels in 2015. Service levels within the Kitchener Corridor study area are as follows: • 30 revenue GO diesel trains per day, each powered by 1 locomotive; • 4 non-revenue GO diesel trains per day, each powered by 1 locomotive; and • 2 CN Freight diesel trains per day. For the future scenario, the TSS1 service levels account for operational and safety considerations and regulations that limit the service levels achievable with a given infrastructure design. Current rail regulations are principally governed by Transport Canada and the US Federal Rail Administration. Rail policy has also been developed by the American Railway Engineering and Maintenance of Way Association (AREMA) and the American Public Transportation Association (APTA). Metrolinx, Canadian National (CN) and Canadian Pacific (CP) Railway have also established additional operational policies, standards, and rules to ensure safe and reliable service. Collectively, these regulations and policies dictate how railways are designed, operated and maintained. To expand rail service, the regulations and policies have to be considered. If the existing infrastructure does not allow expanded service, then new infrastructure must be considered. Service goals represent long term planning upon which infrastructure plans are developed. In the TSS1 scenario, the train fleet travelling on the Kitchener Corridor will be both electric and diesel. The projected future service levels of diesel trains travelling on the Kitchener Corridor study area, which include a 10% safety factor, are as follows: • 72 GO diesel revenue trains per day, each powered by 2 locomotives; • 92 GO diesel revenue trains per day, each powered by 1 locomotive; • 0 GO diesel non-revenue trains per day; • 4 VIA trains per day; and • 4 CN Freight diesel trains per day. In the TSS1 schedule, the morning peak was assumed to be 3 hours long, from 7AM to 10AM, and the afternoon peak was assumed to be 4 hours long, from 3PM to 7PM.

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3 Local Air Quality Assessment

3.1 Air Contaminants and Thresholds The air contaminants considered in the local air quality assessment are as follows: • Carbon monoxide (CO);

• Nitrogen dioxide (NO2);

• Respirable Particulate Matter (PM2.5);

• Inhalable Particulate Matter (PM10);

• Benzene (C6H6);

• Benzo(a)pyrene (B(a)P) (C20H12);

• 1,3-Butadiene (C4H6);

• Formaldehyde (CH2O);

• Acetaldehyde (CH3CHO); and

• Acrolein (C3H4O). These are the key air contaminants associated with diesel combustion, and those agreed with Metrolinx to be included in the studies. The local air quality assessment involves predicting maximum and average concentrations of these contaminants and comparing the concentrations to objectives that have been established either provincially or nationally. The relevant objectives are the Ontario Ambient Air Quality Criteria (AAQC) and the Canadian Ambient Air Quality Standards (CAAQS). Table 1 shows the applicable AAQC and CAAQS objectives. AAQCs represent desirable concentrations of air contaminants. They are commonly used in environmental assessments. They are not statutory limits. Ontario’s regulation dealing with local air quality (O. Reg. 419/05) exempts motor vehicles, including locomotives. The CAAQS are used by provinces and territories to guide air zone management actions. They are not intended as facility level regulatory standards, and measures mandated to achieve the CAAQS should consider technical achievability, practicality and implementation costs (CCME, 2019).

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TABLE 1: AIR QUALITY OBJECTIVES

Contaminant Averaging Period Objective (µg/m3) AAQC 1 hour 36,200 CO 8 hours 15,700 1 hour 400 NO2 24 hours 200

PM10 24 hours 50 24 hours 2.3 Benzene Annual 0.45 24 hours 5.0E-05 Benzo(a)pyrene Annual 1.0E-05 24 hours 10 1,3-Butadiene Annual 2 Formaldehyde 24 hours 65 Acetaldehyde 24 hours 500 1 hour 4.5 Acrolein 24 hours 0.4 CAAQS 1-hour [1] 119 NO2 (2020) Annual [2] 34 1-hour [1] 83 NO2 (2025) Annual [2] 24 24 hours [3] 27 PM2.5 (2020) Annual [4] 8.8 [1] The 3-year average of the annual 98th percentile daily maximum 1-hour average concentrations. [2] The average over a single calendar year of all the 1-hour average concentrations. [3] The 3-year average of the annual 98th percentile of the daily 24-hour average concentrations. [4] The 3-year average of the annual average concentrations. 3.2 Background Air Quality Background concentrations of air contaminants were estimated and added to the model-predicted concentrations produced by rail operations. This provided a prediction of cumulative concentrations of air contaminants. Background air quality concentrations were estimated using historical air quality monitoring data from provincial and federal air quality monitoring stations that best represent the study area. The resulting background concentrations were used for both the baseline and future scenario. Since air contaminant concentrations have declined in Southern Ontario for many years and are likely to continue to decline in the coming years, the use of these concentrations for the future scenario is considered to be a worst-case approach. From 2008 to 2017, for example, the annual average concentration of NO2 declined by 26% and the annual average concentration of PM2.5 declined by 3% in Downtown Toronto (MECP, 2017). The monitoring stations used to determine background air quality concentrations for the air quality study area can be seen in Appendix B.

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For NO2 and PM2.5, the available monitoring data consisted of continuous hourly values. The data allowed for estimating background concentration by hour of day. As background concentrations vary widely from day to day, a 90th percentile concentration was calculated for each hour of the day using 5 years of hourly monitoring data. The resulting background concentrations represented the highest background conditions likely to coincide with maximum predicted concentrations from rail operations.

They were used when predicting maximum 1-hour and/or 24-hour cumulative concentrations of NO2 and PM2.5. For other contaminants, the background monitoring data consisted of 24-hour samples. The data did not allow for estimating background concentrations by hour of day. Instead, a 90th percentile 24- hour concentrations were calculated from 5 years of monitoring data and used to represent background conditions when predicting maximum 24-hour cumulative concentrations. When predicting annual average cumulative concentrations, annual average concentrations from the monitoring data were used to represent background conditions. Tables 2 and 3 present background concentrations for all contaminants and relevant averaging times. The th 90 percentile 24-hour concentrations for NO2 and PM2.5 were determined using data from the Toronto Downtown monitoring station for the years 2013 to 2017. Detailed information on the background air quality data for each contaminant and the corresponding monitoring stations has been provided in Appendix B. TABLE 2: SUMMARY OF BACKGROUD CONCENTRATION LEVELS IN STUDY AREA

Background concentrations Contaminant Averaging Time (µg/m3) 1 hour 219 CO 8 hours [2] 1189

NO2 Annual 28

PM2.5 Annual 8.0 PM10 [1] 24 hours 26 24 hours 0.80 Benzene Annual 0.52 24 hours 9.5E-05 Benzo(a)pyrene Annual 5.5E-05 24 hours 0.07 1,3-Butadiene Annual 0.04 Formaldehyde 24 hours 3.5 Acetaldehyde 24 hours 1.7 1 hour [3] 0.12 Acrolein 24 hours 0.07

[1] Ambient Background Level estimated from PM2.5 levels using published emission factors (Lall et al., 2004) [2] 90th percentile 8-hour ambient CO data was not available; the maximum 8-hour concentration from NAPS Station 60430 –Toronto West and NAPS Station 60440 - Toronto North was used [3] 1-hr average ambient acrolein data was not available; the maximum 24-hr concentration from NAPS Station 62601- Experimental Farm, Simcoe, ON was used.

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TH TABLE 3: 90 PERCENTILE BACKGROUND NO2 AND PM2.5 CONCENTRATIONS BY HOUR OF DAY

3 Hour of Day NO2 (ppb) PM2.5 (µg/m )

1 26 16 2 26 16 3 26 16 4 26 16 5 26 16 6 27 17 7 30 16 8 32 16 9 31 16 10 27 16 11 23 16 12 20 16 13 19 15 14 18 14 15 18 14 16 18 14 17 19 14 18 20 15 19 21 15 20 23 15 21 24 16 22 25 15 23 26 15 24 26 15

A comparison of background concentrations to the applicable AAQC’s and CAAQS shows that the background concentrations generally meet the air quality objects, with the exception of Benzo(a)pyrene and annual average benzene concentrations. This situation with the latter two air contaminants is not unique to the study area. It is widespread across Southern Ontario. 3.3 Receptors Receptors for this assessment include the following sensitive land uses: • Residences; • Schools, universities, libraries and daycare centres; • Hospitals and clinics, nursing / retirement homes; and • Churches and places of worship.

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Receptors were included within 300 m of the rail line. In general, receptors were identified using publicly available address point databases or through visual identification using publicly available satellite aerial images. During the review of aerial images, if construction was visible that was thought to potentially be for a sensitive use building, it was included in the assessment. For residential buildings up to two stories in height, receptors were included at a height of 1.5 m above the ground. Buildings greater than two stories include receptors at every 3 m along the building façade. Within 150 m of the rail corridor, all buildings with sensitive land use were included as receptors in the assessment. However, where a number of residential buildings with the same building height were clustered together, the residence with the façade closest to the rail corridor was selected as a representative receptor. It was assumed that this receptor represents the worst-case air quality impacts for all buildings in the cluster. This method of receptor selection was adopted in order to reduce the redundancy of residential receptors within densely populated urban and suburban areas. Beyond 150 m from the rail line, receptors were placed in a 100 m grid within the study area, up to 300 m. Figure 3 shows the receptor locations in the study area.

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FIGURE 3: RECEPTOR LOCATIONS IN THE KITCHENER AIR QUALITY STUDY AREA

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3.4 Sources of Emissions Sources accounted for in the dispersion modelling conducted for the local air quality study were as follows: • Moving diesel locomotives, throughout the study area. The assumed configuration of engines on all diesel trains was a main locomotive engine for motive power, and a generator, known as a Head End Power (HEP) unit, to provide electricity to passenger cars for lighting, heating/cooling, etc. 3.5 Model Selection Dispersion modelling was conducted using the US EPA’s dispersion modelling software, AERMOD1. Dispersion models use mathematical formulas to represent the atmospheric processes that transport and disperse contaminants emitted by a source. AERMOD is a steady-state dispersion model, designed to predict air contaminant concentrations at receptors located within several kilometers of a source. AERMOD has been adopted by the Province of Ontario as an approved dispersion model for regulatory purposes. The use of steady-state dispersion models to model emissions from transportation corridors is a widely accepted practice. The US EPA provides guidance on how to assess transportation sources within AERMOD. 3.5.1 Terrain Data Terrain data was included in the AERMOD model to take into consideration the elevation differences between the railway, receptors, and intervening terrain. The topographical features were assumed to be the same in the Baseline and Future Scenario. High resolution topographical information was obtained from the Ontario Ministry of Environment, Conservation, and Parks (MECP) database. 3.5.2 Meteorological Data Site specific meteorological data were processed for input to the AERMOD model. Fully processed 5- year (2013-2017) site-specific meteorological data were prepared in-house at RWDI. Upper air weather data were obtained from the upper air monitoring station at Buffalo, New York, and surface weather data were obtained from Pearson Airport2. 3.5.3 Chemical Transformation of Nitrogen Oxides Exhaust from diesel fuel combustion contains a group of contaminants referred to as the oxides of nitrogen (NOX). The NOX in diesel exhaust is comprised mainly of nitric oxide (NO) and nitrogen dioxide (NO2). Shortly after combustion, the diesel exhaust is dominated by NO. However, once the exhaust is emitted to the atmosphere and starts mixing with the air, some of the NO is oxidized in reactions with other contaminants – primarily ground-level ozone (O3) – to produce NO2. For the local air quality study, the Ozone Limiting Method (OLM) was used to estimate the short-term concentration of NO2 resulting from emissions of NOX. Under the OLM, concentrations of NOX predicted by AERMOD are converted to NO2 based on the background ozone concentration. To represent background ozone conditions, 90th percentile ozone concentrations by hour of day were derived from measurements recorded by the MECP at the Toronto Downtown monitoring station (years 2013-2017). Table 4 shows the resulting ozone concentrations.

1 AERMOD version 16216 was used for this assessment. The Ministry of Ontario updated from AERMOD version 16216 to AERMOD version 19191 while the project was ongoing, and some modelling had been completed. Modelling was continued using AERMOD version 16216 to remain consistent in the assessment. 2 As per the methodology outlined in the “Air Dispersion Modelling Guideline for Ontario, Guideline A-11, version 3.0, February 2017”, the calms were removed and replaced by a wind speed value of 1 m/s. The associated wind directions were randomized.

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TH TABLE 4: 90 PERCENTILE VARYING HOURLY BACKGROUND CONCENTRATIONS FOR O3

Hour of Day O3 (ppb)

1 38 2 37 3 36 4 35 5 34 6 32 7 30 8 30 9 32 10 36 11 39 12 43 13 47 14 49 15 50 16 50 17 50 18 50 19 47 20 45 21 42 22 40 23 39 24 38 3.6 Rail Activity Modelling 3.6.1 Emission Factors All locomotives were assumed to emit contaminants at rates corresponding to the regulatory emission limits. The US EPA has sets of standards for emissions from various internal combustion sources including locomotives and generators. Railway operations in Canada comply with these standards through the Railway Safety Act. These standards are phased in through a tiered approach, where Tier 0 is the least stringent (highest emissions) and Tier 4 is the most stringent (lowest emissions). GO Transit currently uses a mix of diesel-powered locomotives ranging from Tier 0 to Tier 4. For each tier, the US EPA provides emission factor limits (g/bhp-hr) for CO, PM10, NOX, and hydrocarbons (HC) applicable to locomotive and HEP engines.

These emission factor limits were used to estimate emissions. PM2.5 emissions were calculated as a fraction of the PM10 emissions. Emissions of acrolein, benzene, formaldehyde, acetaldehyde, and 1,3- butadiene were calculated as fractions of total volatile organic compounds (VOCs), which in turn are calculated as a fraction of the total HC. Benzo(a)pyrene emissions were calculated as a fraction of the PM10 emissions. The necessary speciation fractions were obtained from US EPA data on speciation of diesel exhaust emissions. The speciation fractions are shown in Table 5 below.

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TABLE 5: SPECIATION FACTORS FOR PM2.5, PAHs, VOCs, AND CARBONYLS

Contaminant Tier 0 Tier 2 Tier 3 Tier 4

VOC [1] 1.05 x HC

[1] PM2.5 0.97 x PM10

Acrolein [2] 3.0E-02 x VOC 1.9E-02 x VOC 1.9E-02 x VOC 1.0E-03 x VOC

Benzene [2] 2.0E-02 x VOC 5.4E-02 x VOC 5.4E-02 x VOC 5.4E-02 x VOC

[2] Benzo(a)pyrene 2.1E-06 x PM10 6.7E-06 x PM10 6.7E-06 x PM10 6.7E-06 x PM10

Formaldehyde [2] 2.1E-01 x VOC 2.9E-01 x VOC 2.9E-01 x VOC 2.9E-01 x VOC

Acetaldehyde [2] 7.5E-02 x VOC 1.0E-01 x VOC 1.0E-01 x VOC 1.0E-01 x VOC

1,3 Butadiene [2] 1.9E-03 x VOC 1.9E-03 x VOC 1.9E-03 x VOC 1.9E-03 x VOC

[1] Emission Factors for Locomotives”, U.S. EPA Office of Transportation and Air Quality, EPA-420-F-09-025, April 2009, p.4 [2] Speciation Profiles and Toxic Emission Factors for Non-Road in MOVES2014b, July 2018, p. 16 & p. 18 In order to quantify emissions from the diesel emissions from the GO Transit fleet, a weighted average approach was taken where the emission factors associated with specific tiers were weighted based on the number of locomotives from that respective tier within the locomotive fleet. The GO Transit fleet distribution is based on information provided by Metrolinx, and is shown in Tables D-4 and D-5 in Appendix D. Table 6 shows the weighted emission factors estimated to represent emission from diesel- powered locomotives and HEP units. More information on the derivation of emission factors can be found in Appendix D. TABLE 6: TIER-WEIGHTED EMISSION FACTORS

Weighted HEP Unit Weighted Locomotive Contaminant Emission Factor (g/bhp- Emission Factor (g/bhp-hr) hr) CO 1.8 2.6

PM10 0.16 0.13 NOX 4.9 4.4 PM2.5 0.15 0.13 Acrolein 7.4E-03 1.1E-02 Benzene 1.6E-02 2.6E-02 Benzo(a)pyrene 9.7E-07 8.0E-07 Formaldehyde 9.4E-02 1.5E-01 Acetaldehyde 3.4E-02 5.3E-02 1,3-Butadiene 6.5E-04 1.0E-03

The tier-weighted emission factors are assumed to apply also to freight trains in the Baseline and Future Scenario, as well as VIA Rail trains in the Baseline and Future Scenario. 3.6.2 Emission Calculation The following subsections provide details on the methodology for the calculation of emission rates for the different source types.

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3.6.2.1 Moving Trains In dispersion models, emissions from moving vehicles such as locomotives are represented as if coming from stationary sources distributed along the route of travel. This approach is based on guidance from the US EPA. The route is divided into short segments, referred to as volume sources, and each segment is treated as a stationary source. The emission from each volume source corresponds to the amount of emissions produced by the vehicles while travelling on that segment of the route. In the present case, the emission rate for each volume source was calculated based on the number of trains expected to pass through each hour, the expected speed of these trains, the length of the segment, and the engine load factor (brake horsepower) at that location. These calculations required hour-by-hour information on the number of trains travelling along the corridor. This hourly distribution of trains was determined through train-by-train projections of departure and arrival times provided by Metrolinx. Existing GO trains were assumed to be comprised of one diesel locomotive and 12 cars. In the future scenario, the TSS1 schedule includes both trains with one diesel and two diesel locomotives on the Kitchener Corridor. The hour-by-hour distribution of trains for the Baseline and Future Scenarios is presented in Appendix C. The calculations also required the engine brake horsepower and train speed to be distributed along the section of rail corridor that was modelled. This was done using sample trip log data provided by Metrolinx, which shows typical train speeds and engine throttle notch settings at various points along the corridor. Table 7 relates the throttle notch settings to brake horsepower for an MP-40 locomotive. It was assumed that this relationship between notch settings and brake horsepower applies to all train engines (GO, VIA and CN Freight) in both the Baseline and Future Scenarios. TABLE 7: NOTCH SETTING AND CORRESPONDING BRAKE HORSEPOWER FOR MP-40 [1] LOCOMOTIVE Notch L. Idle Idle DB [2] 1 2 3 4 5 6 7 8 BHP 9.0 27.8 46.7 231.6 448.7 982.9 1,445 1,876 2,878 3,658 4,230 [3] NOX (g/h) 44 137 230 1143 2214 4851 7131 9258 14203 18053 20876 [3] PM2.5 (g/h) 1.4 4.3 7.2 36 69 152 223 289 444 564 652 [1] Data from an MP40PH-3C EMD 16-710G3C-T2 engine test on 12/11/07 [2] DB = Dynamic Braking [3] Emission rates are estimated fleet-average emissions rates based on the emission factors described in Section 3.6.1 Mean values of speed and notch settings were assigned to sections of the study area segments based on trends in the data provided by Metrolinx. Table 8 shows the assumed mean speeds and notch settings for trains operating within the modelled segments of the Kitchener Corridor.

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TABLE 8: AVERAGE GO TRAIN SPEED AND HORSEPOWER FOR STUDY AREA

Distance from Speed Direction Study Segment Strachan Ave Notch BHP (km/hr) (km) > 11.1 102 6 2,878 East of Etobicoke Station to Weston Station 10.8 - 11.1 34 1 232 4.3 - 10.8 95 5 1,876 Weston Station to Bloor Station 4.0 - 4.3 35 1 232 Eastbound Bloor Station to Strachan Avenue < 4.0 57 3 983 > 22.3 47 1 232 East of Bramalea Station to West of Malton Station 21.8 - 22.3 58 6 2,878 < 21.8 54 1 232 < 3.7 56 5 1,876 Strachan to Bloor Station 3.7 – 4.0 26 1 232 4.0 – 10.5 88 7 3,658 Bloor Station to Weston Station Westbound 10.5 – 10.8 40 1 232 Weston Station to Etobicoke Station > 10.8 72 8 4,230 21/4 - 21.6 42 7 3,658 West of Malton Station to East of Bramalea Station 21.6 - 22.6 48 1 232

The HEP unit is assumed to operate at a constant brake horsepower. For the purposes of this modelling scenario, the HEP units were assumed to operate at 50% of total load (600 bhp) whenever the trains are in operation. This assumption was confirmed by Metrolinx on December 18, 2019, and is assumed to apply to both the Baseline and Future Scenario. The height of each volume source height was set at 9.44 m, which is twice the GO train locomotive height. The release height was taken to be half of the source height, at 4.72 m. Where the Kitchener rail corridor included train traffic from other Metrolinx train lines, namely the Barrie and Milton lines, parallel volume sources were used to separate emissions. The width of the volume sources was selected in order to encompass the width of the rail tracks with trains travelling on the tracks. In certain areas, the volume source width was reduced to maintain an adequate separation distance from the volume sources and the nearest sensitive receptors (as per US EPA guidance published in US EPA-420-B-15-084). Figure E.1 in Appendix E shows an example of the configuration of volume sources in AERMOD. Further information and sample calculations for emissions from moving trains are presented in Appendix D.

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4 Modelling Results

4.1 Overview Results will be presented in the following sequence. 1. The predicted maximum cumulative concentrations of all contaminants, under worst-case meteorological conditions, at the worst-case receptor location(s) in the study area are presented in tabular form. This information is used to identify which contaminants, if any, are predicted to exceed one or more air quality standards or criteria. 2. For selected contaminants identified as exceeding one or more standards or criteria, the following additional information is provided: a. Plots showing the spatial pattern of maximum and average concentrations within the study area; b. Graphs showing the frequency distribution of hourly cumulative concentrations at selected receptor locations; c. A table showing the breakdown of average individual contributions from Metrolinx-related emission sources and other background sources to cumulative concentrations at a selection of receptors; d. A table showing the range of predicted concentrations at a selection of receptor locations, rather than just the maximum concentration at the worst-case receptor under worst-case meteorological conditions. 4.2 Worst-Case Cumulative Concentrations The highest predicted cumulative concentrations at the worst-case receptor, under worst-case meteorological conditions and reasonably worst-case background air quality conditions are summarized in Tables 9 (Baseline Scenario) and 10 (Future Scenario). Some of the contaminants are predicted to exceed standards or criteria at the worst-case receptor, as follows:

PM2.5, PM10, Acrolein, Carbon Monoxide, Formaldehyde, Acetaldehyde, and 1,3-Butadiene are all predicted to be within the provincial air quality criteria (AAQCs) in both the Baseline and Future Scenario. As mentioned previously, the AAQCs and CAAQS represent desirable levels, rather than statutory limits. Measures mandated to achieve the CAAQS should consider technical achievability, practicality and implementation costs (CCME, 2019). Figures 4 and 5 show where the worst-case receptors are located for the contaminants that exceed an AAQC or CAAQS. They are immediately adjacent to the rail corridor.

The following subsections provide more detail on predicted concentrations of NO2, Benzene and Benzo(a)pyrene, all of which are predicted to exceed one or more AAQC or CAAQS at the worst-case receptor(s).

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TABLE 9: MAXIMUM MODELLED CONCENTRATIONS FOR BASELINE (2015) SCENARIO

Contribution from Ambient Background Maximum Cumulative Percentage of Pollutant Averaging Time Modelled Sources Objective (μg/m³) Level (μg/m³) Concentration (μg/m³) Criterion (μg/m³)

AAQC 1 hour 28 56 84 400 21% NO2 24 hours 5.4 41 46 200 23% 1 hour 0.051 0.12 0.17 4.5 3.8% Acrolein 24 hours 0.011 0.07 0.079 0.4 20% 1 hour 13 219 232 36200 0.6% CO 8-hr 3.9 1189 1193 15700 7.6%

PM10 24 hours 0.19 26 26 50 52% 24 hours 0.023 0.80 0.84 2.3 36% Benzene Annual 0.0075 0.52 0.53 0.45 118% 24 hours 1.1E-06 9.5E-05 9.6E-05 5.0E-05 192% B(a)pyrene Annual 3.5E-07 5.5E-05 5.5E-05 1.0E-05 554% Formaldehyde 24 hours 0.14 3.5 3.6 65 6% Acetaldehyde 24 hours 0.049 1.7 1.8 500 0.4% 24 hours 0.00094 0.07 0.068 10 0.7% 1,3-Butadiene Annual 0.00030 0.039 0.040 2.0 2.0% CAAQS [2] 1 hour (2020) 28 56 84 119 71% 1 hour (2025) 28 56 84 83 101% NO2 Annual (2020) 1.7 28 47 34 139% Annual (2025) 1.7 28 47 24 197% 24 hours 0.13 14 14 27 52% PM2.5 Annual 0.059 8.0 8.1 8.8 92% [1] Background levels based on difference between receptor concentration with and without background concentrations in model [2] Results averaged based on CAAQS averaging periods described in Table 1.

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TABLE 10: MAXIMUM MODELLED CONCENTRATIONS FOR FUTURE SCENARIO

Contribution from Ambient Background Maximum Cumulative Threshold Pollutant Averaging Time Modelled Sources Percentage of Criteria Level (μg/m³) Concentration (μg/m³) (μg/m³) (μg/m³)

AAQC 1 hour 81 47 128 400 32% NO2 24 hours 32 41 73 200 36% 1 hour 0.18 0.12 0.3 4.5 7% Acrolein 24 hours 0.064 0.07 0.13 0.4 33% 1 hour 44 219 263 36200 0.7% CO 8-hr 24 1189 1213 15700 7.7%

PM10 24 hours 1.1 26 27 50 54% 24 hours 0.14 0.80 0.94 2.3 41% Benzene Annual 0.055 0.52 0.58 0.45 129% 24 hours 7.0E-06 9.5E-05 1.0E-04 5.0E-05 204% B(a)pyrene Annual 2.7E-06 5.5E-05 5.8E-05 1.0E-05 577% Formaldehyde 24 hours 0.84 3.5 4.3 65 7% Acetaldehyde 24 hours 0.30 1.7 2.0 500 0.4% 24 hours 0.0058 0.07 0.1 10 0.7% 1,3-Butadiene Annual 0.0022 0.039 0.041 2.0 2.1% CAAQS [2] 1 hour (2020) 81 45 126 119 106% 1 hour (2025) 81 45 126 83 152% NO2 Annual (2020) 32 28 58 34 171% Annual (2025) 32 28 58 24 242% 24 hours 0.83 14 15 27 55% PM2.5 Annual 0.43 8.0 8.5 8.8 96% [1] Background levels based on difference between receptor concentration with and without background concentrations in model [2] Results averaged based on CAAQS averaging periods described in Table 1.

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FIGURE 4: LOCATIONS OF WORST-CASE RECEPTORS IN BASELINE SCENARIO

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FIGURE 5: LOCATIONS OF WORST-CASE RECEPTORS IN FUTURE SCENARIO

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4.3 Nitrogen Dioxide (NO2)

th Figures 6 and 7 are plots of cumulative annual average NO2 and cumulative 98 percentile 1-hour NO2 concentrations in the study area. The insets in the figures show how concentrations vary with distance away from the tracks.

The figures show that the predicted cumulative concentrations of NO2 decline sharply within the first 150 m from the rail corridor. The decline is slower further away as levels start to approach background th concentrations. The predicted future daily maximum 1-hour NO2 levels (98 percentile) fall within the 2020 CAAQS objective at approximately 50 m from the rail corridor, and within the 2025 CAAQS objective at approximately 100 m from the rail corridor. The predicted future annual average concentrations remain above the 2020 and 2025 CAAQS objective at all distances within the study area. This is because the background level of annual NO2 used in the analysis is above the 2025 CAAQS objective.

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FIGURE 6: FUTURE MAXIMUM ANNUAL NO2 IN STUDY AREA

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TH FIGURE 7: FUTURE MAXIMUM 98 PERCENTILE DAILY MAXIMUM 1-HOUR NO2 IN STUDY AREA

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Four representative receptors were selected to provide additional information on predicted NO2 concentrations in the study area. The selected receptor locations are shown in Figure 8 and listed in Table 11. The receptors represent a range of distance and direction from the rail line. Receptor 1 is the future scenario worst-case receptor, as seen in Figure 5 above. TABLE 11: SELECTED REPRESENTATIVE RECEPTOR LOCATIONS

Receptor Distance from Rail Height (m) Comments ID Corridor (m) Residential receptors north of tracks, centre 1 1.5 55.0 of study area

2 1.5 30.0 Future scenario worst-case receptor Residential receptors south of tracks, centre 3 1.5 95.0 of study area Residential receptors south of tracks, west 4 1.5 145.0 end of study area Residential receptors north of tracks, east 5 1.5 130.0 end of study area Residential receptors south of tracks, east 6 1.5 245.0 end of study area Green space receptor north of tracks, west 7 1.5 175.0 end of study area Residential receptor north of tracks, east 8 1.5 255.0 end of study area Baseline scenario 8-hour averaging period 9 1.5 30.0 worst-case receptor Residential receptor north of tracks, centre 10 1.5 45.0 of study area

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FIGURE 8: LOCATIONS OF REPRESENTATIVE RECEPTORS

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Table 12 shows the range of predicted cumulative 1-hour concentrations of NO2 at the 4 representative receptor locations. The maximum/minimum concentrations shown in the table are maximum/minimum values over the 5-year period of the simulation. Similarly, mean values are 5-year mean values. All values in the table include hourly 90th percentile background concentrations. The table shows that, at most of the representative receptors, the maximum hourly concentrations increase by 14% to 62% between the Baseline and Future Scenario, but the mean and median concentrations change by less than 10%, except at Receptors 1, 2, 9, and 10 (receptors directly adjacent to the tracks), where the mean increases between 16% and 22%, respectively.

TABLE 12: RANGE OF PREDICTED CUMULATIVE 1-HOUR NO2 AT SELECTED RECEPTORS

Hourly Concentration (µg/m3) Height Distance Above Scenario Receptor from Tracks Grade (m) Maximum Mean Median Minimum (m)

1 1.5 55 75 46 47 34 2 1.5 30 84 47 48 34 3 1.5 95 69 46 46 34 4 1.5 145 67 45 46 34 5 1.5 130 66 45 46 34 Baseline 6 1.5 245 65 45 46 34 7 1.5 175 65 45 46 34 8 1.5 255 63 45 46 34 9 1.5 30 84 47 48 34 10 1.5 45 77 46 48 34 1 1.5 55 118 53 50 34 2 1.5 30 128 57 53 34 3 1.5 95 95 50 49 34 4 1.5 145 87 47 48 34 5 1.5 130 84 49 49 34 Future 6 1.5 245 78 47 48 34 7 1.5 175 78 48 49 34 8 1.5 255 72 47 48 34 9 1.5 30 128 57 53 34 10 1.5 45 125 55 51 34

Ontario AAQC 400 (1-hr), 200 (24-hr) 2020 CAAQS 119 (98th percentile daily max 1-hr) 2025 CAAQS 83 (98th percentile daily max 1-hr)

Appendix F shows frequency distributions of predicted cumulative hourly NO2 concentrations at the four representative receptors. Like the values in Table 12, the concentrations shown in these graphs are the sum of predicted contribution from modelled emission sources and the 90th percentile background concentration. The graphs show that the predicted hourly concentrations in the Future Scenario are below the 2020 CAAQS

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99% of the time at Receptors 2, 9, and 10 which are adjacent to the train tracks, and 100% of the time at all the other representative receptors. They are below the 2025 CAAQS between 92% to 99% of the time at Receptors 1, 2, 3, 5, 9, and 10, and below the 2025 CAAQS 100% of the time at all other representative receptors. Table 13 shows the contributions of Metrolinx-related emission sources and background sources to the average cumulative NO2 concentrations at the representative receptors. The background concentrations shown in this table are average levels, rather than 90th percentile. The Metrolinx contributions shown in the table include a very small contribution from other trains on the corridor as well (VIA Rail and freight).

The table shows that the average NO2 concentration is dominated by the background contribution at all receptors, except Receptors 2 and 9 in the Future Scenario, where the concentration is dominated by the rail corridor. The average contribution of Metrolinx-related emission sources is higher in the Future Scenario than in the Baseline Scenario, but remains small compared to background, except at Receptors 2 and 9, which are adjacent to the rail corridor.

TABLE 13: SOURCE CONTRIBUTIONS TO AVERAGE NO2 AT SELECTED RECEPTORS

5-Year Average Concentration (µg/m3) Height Distance Above Scenario Receptor from Tracks Metrolinx- Grade (m) related Background Total (m) Sources 1 1.5 55 1.1 28 29 2 1.5 30 1.7 28 30 3 1.5 95 0.6 28 29 4 1.5 145 0.3 28 28 5 1.5 130 0.4 28 28 Baseline 6 1.5 245 0.2 28 28 7 1.5 175 0.3 28 28 8 1.5 255 0.2 28 28 9 1.5 30 1.7 28 30 10 1.5 45 1.3 28 29 1 1.5 55 8 28 36 2 1.5 30 12 28 40 3 1.5 95 5 28 33 4 1.5 145 2 28 30 5 1.5 130 3 28 31 Future 6 1.5 245 2 28 30 7 1.5 175 2 28 30 8 1.5 255 2 28 30 9 1.5 30 12 28 40 10 1.5 45 9 28 37 2020 CAAQS 34 (Annual Average) 2025 CAAQS 24 (Annual Average)

30 Revision DE 03-Dec-2020 GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

4.4 Benzene and Benzo(a)Pyrene Table 14 shows the individual contributions of Metrolinx-related emission sources and background sources to the predicted average cumulative Benzene concentrations. The predicted average concentrations of Benzene are dominated by the background contribution. The contribution from Metrolinx-related emission sources to the cumulative Benzene concentrations is small. In the Future Scenario, it is 9% at Receptors 2 and 9, and less than 7% at all other representative receptors. The overall cumulative Benzene concentration at all receptors increases by approximately 1-9% at all representative receptors between the Baseline and Future Scenarios. TABLE 14: SOURCE CONTRIBUTIONS TO AVERAGE BENZENE AT SELECTED RECEPTORS

5-Year Average Concentration (µg/m3) Height Distance Scenario Receptor above from Tracks Metrolinx- Grade (m) (m) related Background total Sources

1.5 1 55 0.0048 0.52 0.52 1.5 2 30 0.0073 0.52 0.53 1.5 3 95 0.0027 0.52 0.52 1.5 4 145 0.0014 0.52 0.52 1.5 5 130 0.0019 0.52 0.52 Baseline 1.5 6 245 0.0009 0.52 0.52 1.5 7 175 0.0014 0.52 0.52 1.5 8 255 0.0009 0.52 0.52 1.5 9 30 0.0072 0.52 0.53 1.5 10 45 0.0056 0.52 0.53 1.5 1 55 0.036 0.52 0.56 1.5 2 30 0.053 0.52 0.57 1.5 3 95 0.0212 0.52 0.54 1.5 4 145 0.0109 0.52 0.53 1.5 5 130 0.0153 0.52 0.54 Future 1.5 6 245 0.0073 0.52 0.53 1.5 7 175 0.0112 0.52 0.53 1.5 8 255 0.0073 0.52 0.53 1.5 9 30 0.0526 0.52 0.57 1.5 10 45 0.0412 0.52 0.56

Ontario AAQC 0.45 (annual mean)

Table 15 shows the same information as Table 14, but for Benzo(a)Pyrene. The average concentrations are dominated by the background sources. Like Benzene, the contribution of Metrolinx related sources to the cumulative concentrations of Benzo(a)Pyrene is small. In the Future Scenario, it is approximately 5% at Receptor 2 and 9, and less than 4% at all other representative receptors. Similar to Benzene, the overall cumulative concentration at all representative receptors increase by approximately 1-4% between the Baseline and Future Scenarios.

31 Revision DE 03-Dec-2020 GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

TABLE 15: SOURCE CONTRIBUTIONS TO AVERAGE BENZO(A)PYRENE AT SELECTED RECEPTORS

Annual Average Concentration (ng/m3) Height Distance above Scenario Receptor from Tracks Metrolinx- Grade (m) related Background Total (m) Sources 1 1.5 55 2.36E-04 0.055 0.055 2 1.5 30 3.61E-04 0.055 0.055 3 1.5 95 1.32E-04 0.055 0.055 4 1.5 145 6.48E-05 0.055 0.055 5 1.5 130 9.15E-05 0.055 0.055 Baseline 6 1.5 245 4.16E-05 0.055 0.055 7 1.5 175 6.55E-05 0.055 0.055 8 1.5 255 4.18E-05 0.055 0.055 9 1.5 30 3.56E-04 0.055 0.055 10 1.5 45 2.73E-04 0.055 0.055 1 1.5 55 1.75E-03 0.055 0.057 2 1.5 30 2.60E-03 0.055 0.058 3 1.5 95 1.02E-03 0.055 0.056 4 1.5 145 5.03E-04 0.055 0.056 5 1.5 130 7.22E-04 0.055 0.056 Future 6 1.5 245 3.45E-04 0.055 0.055 7 1.5 175 5.27E-04 0.055 0.056 8 1.5 255 3.45E-04 0.055 0.055 9 1.5 30 2.57E-03 0.055 0.058 10 1.5 45 2.00E-03 0.055 0.057 Ontario AAQC 0.01 (annual mean)

4.5 Mitigation Options Table 16 provides a summary of the key project components/activities, potential effects, mitigation measures, and proposed monitoring activities associated with the GO Rail Network Electrification TPAP Addendum Undertaking.

32 Revision DE 03-Dec-2020 GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

TABLE 16: SUMMARY OF POTENTIAL EFFECTS, MITIGATION MEASURES AND MONITORING – AIR QUALITY Project Project Potential Effect Mitigation Measures Monitoring Component Activities Kitchener • Operations • Exhaust emissions of Mitigation Measures: • On-site inspections will be undertaken to confirm the implementation of the mitigation measures and identify Rail and diesel powered trains • A detailed Operations Air Quality Management Plan will be developed and implemented corrective actions if required. Corridor maintenance contribute to local and to limit the generation and dispersion of airborne particulate matter, NOX and other air • Annually, test train propulsion and auxiliary power units, which produces exhaust emissions and ensure that regional air pollution contaminants associated with the project operations. they remain in compliance with applicable Transport Canada heavy-duty diesel engine exhaust emission • New traction engines or propulsion systems and new auxiliary engines and power units standards for CO, PM, NOx and HC. Engine testing will include: will meet higher emission standards (i.e., Tier 4 diesels rather than lower tier diesels). o Testing at no load • Engines and their emission control equipment will be maintained to manufacturers’ o Testing at 50% load specifications. o Testing at 100% load • Rebuilt diesel engines will meet Tier 4 emission standards at the time of major engine • Test rebuilt traction and auxiliary power diesel engines, before being placed into service, to the exhaust rebuilds. emission standards they are rebuilt to meet. • Unnecessary train / engine / propulsion system idling will be minimized through • Develop an Air Sampling and Monitoring Plan and submit an annual report summarizing all sampling and technical and operational measures. monitoring results accumulated over the preceding year. • Unnecessary non-revenue equipment runs will be minimized through design and planning. Mitigation Criteria: • Diesel engines used for traction and auxiliary power in locomotives and DMUs are subject to corresponding US EPA and Transport Canada heavy-duty diesel engine exhaust emission standards for CO, PM, NOx and HC

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5 Conclusion

A worst-case assessment of potential air quality impacts associated with future changes in rail service levels was undertaken. Concentrations of relevant air contaminants were predicted under worst-case meteorological conditions and reasonably worst-case background air quality conditions. This was done for numerous receptor locations, so that the worst-case receptor location(s) could be identified. The analysis was performed using rail service levels that were projected to approximately 2037, with a 10% margin of safety applied on top. The results for the worst-case receptor locations indicated the following:

• 1-hour and 24-hour NO2 meet the current Ontario AAQC’s, but 1-hour and annual average NO2 do not meet the more recent and more stringent Canadian Ambient Air Quality Standards (CAAQS) in either the Baseline or Future Scenario. • 24-hour and annual average Benzo(a)pyrene exceed the provincial AAQCs in both scenarios. • 24-hour Benzene meets the AAQC in both scenarios, but the annual average Benzene does not in either scenario. As mentioned previously, the AAQCs and CAAQS represent desirable levels, rather than statutory limits. Measures mandated to achieve the CAAQS should consider technical achievability, practicality and implementation costs (CCME, 2019).

Further examination of the model results for NO2 showed that the cumulative concentrations decline sharply th within the first 150 m from the rail corridor. The predicted future daily maximum 1-hour NO2 levels (98 percentile) fall within the 2020 CAAQS objective at approximately 50 m from the rail corridor, and within the 2025 CAAQS objective at approximately 100 m from the rail corridor. The predicted future annual average concentrations remain above the 2020 and 2025 CAAQS objective at all distances within the study area. This is because the background level of annual NO2 used in the analysis is above the 2025 CAAQS objective.

A detailed examination of predicted cumulative NO2 concentrations at 10 representative receptors showed that the maximum hourly concentrations increase by 14% to 62% between the Baseline and Future Scenario, but the mean and median concentrations change by less than 10%, except at ground-level locations immediately adjacent to worst-case areas of the corridor (Receptors 1, 2, 9, and 10). The predicted hourly concentrations in the Future Scenario are below the 2020 CAAQS level just below 99% of the time at Receptors 2 and 9, which are adjacent to the rail corridor, and 100% of the time at all the other representative receptors. They are below the 2025 CAAQS level approximately 96% to 99% of the time at Receptors 1, 2, 9, and 10, and 100% of the time at all other representative receptors

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Further examination of the model results for Benzene and Benzo(a)pyrene showed that the predicted contribution of Metrolinx-related sources to the cumulative concentrations is very small (generally less than 10%).

35 Revision DE 03-Dec-2020 GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

APPENDIX A: TSS1 Schedule for Kitchener Corridor

Revision DE 03-Dec-2020 D1L6 D2L12 4EMU Station Route DAY NIGHT DAY NIGHT DAY NIGHT REVENUE GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** ------GO Eastbound UPE Express*** ------Bramalea to Malton GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** ------GO Westbound UPE Express*** ------GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** ------GO Eastbound UPE Express*** ------Malton to Pearson Junction GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** ------GO Westbound UPE Express*** ------GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 Pearson Junction to GO Eastbound UPE Express*** - - - - 64 18 Woodbine GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 GO Eastbound UPE Express*** - - - - 64 18 Woodbine to Weston GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 Weston to St. Clair - Old GO Eastbound UPE Express*** - - - - 64 18 Weston GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 St. Clair - Old Weston to GO Eastbound UPE Express*** - - - - 64 18 Mount Dennis GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 GO Eastbound UPE Express*** - - - - 64 18 Mount Dennis to Bloor GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 GO Eastbound UPE Express*** - - - - 64 18 Bloor to King-Liberty GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 GO Eastbound Local 41 5 28 8 - - GO Eastbound UPE Local** - - - - 64 18 GO Eastbound UPE Express*** - - - - 64 18 King-Liberty to Union GO Westbound Local 41 5 29 7 - - GO Westbound UPE Local** - - - - 64 18 GO Westbound UPE Express*** - - - - 64 18 NON-REVENUE Pearson Station to GO Eastbound Non-Revenue - - - - - 5 Resources Road Equipment Storage GO Westbound Non-Revenue - - - - - 8 Pearson Station to Weston GO Eastbound Non-Revenue - - - - - 3 Station GO Westbound Non-Revenue ------**UPE Local stops at all stops in the UP Express route: Pearson Airport, Woodbine, Weston, St. Clair - Old Weston, Mount Dennis, Bloor, King-Liberty, Union ***UPE Express stops at Pearson, Woodbine, Bloor, and Union Station GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

APPENDIX B: Background Air Quality Concentrations in Study Area

Revision DE 03-Dec-2020 Summary of Background Air Quality Measurements for Carbon Monoxide GO Rail Network Electrification Project

Concentration (ppm) Station ID MOE ID Station Name Location Type Year 1-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 1-hr 8-hr 2013 0.23 0.27 0.36 0.63 0.25 1.41 1.21 2014 0.23 0.27 0.37 0.69 0.26 1.60 1.07 NAPS 60430 MOE 35125 Toronto West 125 Resources Rd. Urban 2015 0.22 0.26 0.36 0.66 0.25 1.30 0.82 2016 0 0 0 1 0.20 1.67 1.23 2017 0 0 0 1 0.20 1.23 0.86 2013 N/A N/A N/A N/A N/A N/A N/A 2014 N/A N/A N/A N/A N/A N/A N/A NAPS 60440 MOE 34021 Toronto North 4905 Dufferin St. Urban 2015 N/A N/A N/A N/A N/A N/A N/A 2016 N/A N/A N/A N/A N/A N/A N/A 2017 0 0 0 1.0 0.20 1.00 0.73 Average - Overall (ppm) 0.11 0.13 0.18 0.83 0.23 1.37 0.99 Average - Overall (µg/m3) 137 161 219 1000 273 1649 1189

Notes: N/A - Data not available. Summary of Background Air Quality Measurements for Nitrogen Dioxide GO Rail Network Electrification Project

Concentration (ppb) Station ID MOE ID Station Name Location Type Year 1-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 1-hr 24-hr 2013 11 16 26 41 14 79 31 2014 12 16 27 50 14 89 48 NAPS 60410 MOE 33003 Toronto East Kennedy Rd. & Lawrence Ave. E. Suburban 2015 11 16 28 46 14 69 38 2016 9 14 25 44 12 68 36 2017 9 13 23 39 12 55 34 2013 14 20 30 46 16 76 38 2014 15 20 31 54 17 83 51 NAPS 60430 MOE 35125 Toronto West 125 Resources Rd. Urban 2015 14 20 31 49 17 63 42 2016 13 19 31 46 16 64 41 2017 13 18 28 43 15 55 41 2013 12 16 24 40 14 60 33 2014 12 16 25 44 14 65 42 NAPS 60433 MOE 31103 Toronto Downtown Bay St. & Wellesley St. W. Urban 2015 11 16 25 41 13 58 33 2016 11 16 25 39 13 57 31 2017 11 15 24 38 13 50 34 Average - Overall (ppb) 12 17 27 44 14 66 38 Average - Overall (µg/m3) 23 33 53 87 28 131 76 Summary of Background Air Quality Measurements for PM2.5 GO Rail Network Electrification Project

Concentration (μg/m3) Station ID MOE ID Station Name Location Type Year 1-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 1-hr 24-hr 2013 7 10 18 33 8.8 75 34 2014 7 10 17 35 9.1 65 35 NAPS 60430 MOE 35125 Toronto West 125 Resources Rd. Urban 2015 7 10 17 32 8.5 58 33 2016 6 8 13 25 7.0 43 24 2017 6 9 14 26 7.4 47 25 2013 6 9 16 34 8.2 64 33 2014 7 10 17 34 8.9 60 33 NAPS 60410 MOE 33003 Toronto East Kennedy Rd. & Lawrence Ave. E. Suburban 2015 6 10 17 33 8.5 60 39 2016 6 8 13 25 7.0 54 27 2017 6 9 14 25 7.4 40 27 2013 7 10 16 30 8.3 75 33 2014 7 10 17 31 8.7 52 33 NAPS 60433 MOE 31103 Toronto Downtown Bay St. & Wellesley St. W. Urban 2015 7 9 17 31 8.4 54 34 2016 6 8 13 23 7.0 36 22 2017 6 9 14 26 7.4 82 28 Average - Overall (µg/m³) 6 9 16 30 8.0 58 31 Summary of Background Air Quality Measurements for Benzo(a)Pyrene GO Rail Network Electrification Project

Concentration (ng/m3) Station ID MOE ID Station Name Location Type Year 24-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 24-hr 2013 0.05 0.07 0.10 0.18 0.06 0.19 2014 0.04 0.05 0.07 0.08 0.04 0.08 NAPS 60427 N/A Toronto - Gage Institute 223 College St. Urban 2015 N/A N/A N/A N/A N/A N/A 2016 N/A N/A N/A N/A N/A N/A 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 N/A N/A N/A N/A N/A N/A NAPS 60430 MOE 35125 Toronto West 125 Resources Rd. Urban 2015 N/A N/A N/A N/A N/A N/A 2016 0.04 0.05 0.09 0.16 0.05 0.19 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 N/A N/A N/A N/A N/A N/A NAPS 60439 N/A Roadside-Wallberg (UofT) 200 College St. Urban 2015 0.060 0.080 0.120 0.160 0.070 0.170 2016 N/A N/A N/A N/A N/A N/A 2017 N/A N/A N/A N/A N/A N/A Average - Overall (ng/m³) 0.048 0.063 0.095 0.145 0.055 0.158

Notes: N/A - Data not available. Summary of Background Air Quality Measurements for Benzene GO Rail Network Electrification Project

Concentration (µg/m3) Station ID MOE ID Station Name Location Type Year 24-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 24-hr 2013 0.44 0.56 0.82 1.04 0.50 1.12 2014 0.44 0.58 0.78 1.14 0.49 1.34 NAPS 60413 N/A Etobicoke West Elmcrest Rd. - Centennial Park Suburban 2015 0.50 0.59 0.67 1.20 0.52 1.42 2016 INS INS INS INS INS INS 2017 N/A N/A N/A N/A N/A N/A 2013 0.57 0.69 0.92 1.47 0.61 2.03 2014 0.58 0.67 0.80 1.09 0.59 1.18 NAPS 60427 N/A Toronto - Gage Institute 223 College St. Urban 2015 N/A N/A N/A N/A N/A N/A 2016 N/A N/A N/A N/A N/A N/A 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 N/A N/A N/A N/A N/A N/A NAPS 60440 MOE 34021 Toronto North 4905 Dufferin St. Urban 2015 N/A N/A N/A N/A N/A N/A 2016 N/A N/A N/A N/A N/A N/A 2017 0.61 0.69 1.06 1.34 0.63 1.46 2013 0.46 0.56 0.86 1.25 0.51 1.27 2014 0.44 0.51 0.77 1.09 0.48 1.36 NAPS 60435 N/A Etobicoke South 461 Kipling Ave. Urban 2015 0.53 0.60 0.66 1.23 0.52 1.40 2016 0.39 0.51 0.76 1.40 0.45 1.48 2017 0.44 0.55 0.72 0.85 0.47 0.86 Average - Overall (µg/m³) 0.49 0.59 0.80 1.19 0.52 1.36

Notes: INS - Insufficient data to calculate valid statistics. N/A - Data not available. Summary of Background Air Quality Measurements for 1,3-Butadiene GO Rail Network Electrification Project

Concentration (µg/m3) Station ID MOE ID Station Name Location Type Year 24-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 24-hr 2013 0.04 0.05 0.08 0.10 0.04 0.11 2014 0.03 0.05 0.07 0.16 0.04 0.17 NAPS 60413 N/A Etobicoke West Elmcrest Rd. - Centennial Park Suburban 2015 0.04 0.06 0.08 0.11 0.05 0.12 2016 INS INS INS INS INS INS 2017 N/A N/A N/A N/A N/A N/A 2013 0.05 0.07 0.09 0.14 0.05 0.14 2014 0.04 0.05 0.07 0.10 0.04 0.10 NAPS 60427 N/A Toronto - Gage Institute 223 College St. Urban 2015 N/A N/A N/A N/A N/A N/A 2016 N/A N/A N/A N/A N/A N/A 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 N/A N/A N/A N/A N/A N/A NAPS 60440 MOE 34021 Toronto North 4905 Dufferin St. Urban 2015 N/A N/A N/A N/A N/A N/A 2016 N/A N/A N/A N/A N/A N/A 2017 0.03 0.04 0.05 0.07 0.03 0.07 2013 0.04 0.05 0.07 0.16 0.04 0.21 2014 0.03 0.04 0.06 0.12 0.04 0.13 NAPS 60435 N/A Etobicoke South 461 Kipling Ave. Urban 2015 0.04 0.05 0.07 0.11 0.04 0.12 2016 0.03 0.03 0.05 0.15 0.03 0.16 2017 0.03 0.04 0.05 0.07 0.03 0.07 Average - Overall (µg/m³) 0.04 0.05 0.07 0.12 0.04 0.13

Notes: INS - Insufficient data to calculate valid statistics. N/A - Data not available. Summary of Background Air Quality Measurements for Formaldehyde GO Rail Network Electrification Project

Concentration (µg/m3) Station ID MOE ID Station Name Location Type Year 24-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 24-hr 2013 N/A N/A N/A N/A N/A N/A 2014 1.83 2.84 4.22 8.60 2.24 9.80 NAPS 60211 N/A Windsor West COLLEGE & SOUTH ST. / 928 SOUTH ST. Suburban 2015 1.26 1.92 3.89 4.19 1.75 4.22 2016 1.55 2.53 3.72 5.55 1.99 5.77 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 1.37 2.37 2.80 3.45 1.68 3.60 NAPS 60439 N/A Roadside-Wallberg (UofT) 200 College St. Urban 2015 2.05 2.96 3.80 5.06 2.25 5.41 2016 1.20 1.72 2.60 3.38 1.42 3.40 2017 N/A N/A N/A N/A N/A N/A Average - Overall (µg/m³) 1.54 2.39 3.51 5.04 1.89 5.37

Notes: N/A - Data not available. Summary of Background Air Quality Measurements for Acetaldehyde GO Rail Network Electrification Project

Concentration (µg/m3) Station ID MOE ID Station Name Location Type Year 24-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 24-hr 2013 N/A N/A N/A N/A N/A N/A 2014 0.95 1.32 2.00 2.38 0.99 2.39 NAPS 60211 N/A Windsor West COLLEGE & SOUTH ST. / 928 SOUTH ST. Suburban 2015 0.78 1.08 1.43 2.32 0.87 2.72 2016 0.99 1.25 1.95 2.36 1.08 2.50 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 0.72 0.97 1.53 2.34 0.88 2.54 NAPS 60439 N/A Roadside-Wallberg (UofT) 200 College St. Urban 2015 1.13 1.28 1.91 2.74 1.13 2.88 2016 0.73 1.20 1.65 2.11 0.91 2.20 2017 N/A N/A N/A N/A N/A N/A Average - Overall (µg/m³) 0.88 1.18 1.74 2.38 0.98 2.54

Notes: N/A - Data not available. Summary of Background Air Quality Measurements for Acrolein GO Rail Network Electrification Project

Concentration (µg/m3) Station ID MOE ID Station Name Location Type Year 24-hr Percentiles Annual MAX 50th 70th 90th 99th Mean 24-hr 2013 N/A N/A N/A N/A N/A N/A 2014 0.02 0.04 0.05 0.09 0.03 0.11 NAPS 60211 N/A Windsor West COLLEGE & SOUTH ST. / 928 SOUTH ST. Suburban 2015 0.03 0.44 0.07 0.14 0.04 0.15 2016 0.03 0.04 0.06 0.09 0.03 0.10 2017 N/A N/A N/A N/A N/A N/A 2013 N/A N/A N/A N/A N/A N/A 2014 0.04 0.05 0.07 0.09 0.04 0.10 NAPS 60439 N/A Roadside-Wallberg (UofT) 200 College St. Urban 2015 0.04 0.06 0.07 0.10 0.05 0.11 2016 0.03 0.04 0.07 0.12 0.03 0.15 2017 N/A N/A N/A N/A N/A N/A Average - Overall (µg/m³) 0.03 0.11 0.07 0.10 0.04 0.12

Notes: N/A - Data not available. GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

APPENDIX C: Baseline (2015) and Future (TSS1) Hourly Rail Service Levels in Kitchener Corridor

Revision DE 03-Dec-2020 Table C.1: Kitchener Corridor Baseline Scenario (2015) Hourly Traffic Volumes for Diesel Locomotives, West of UP Express Pearson Airport Spur Operator Service 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 Daily 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 Total CN Freight Switch Freight ------1 ------1 ------2 Express ------1 ------1 1 ------3 Eastbound Revenue Kitchener Local ------2 2 2 2 1 1 1 1 1 ------13 Westbound Local ------1 1 1 1 1 1 1 1 1 3 1 1 - - - - 14 Non-Revenue Eastbound ------1 ------1 Kitchener Westbound ------1 1 1 ------3

Table C.2: Kitchener Corridor Future Scenario (TSS1-Apr2020) Hourly Traffic Volumes for Diesel Locomotives, West of UP Express Pearson Airport Spur Operator Service 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 Daily 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 Total Eastbound ------1 ------1 ------2 CN Freight Switch Freight D1 Westbound ------1 ------1 ------2 D1L6 3 - - - - 1 - 2 2 4 1 4 4 4 2 1 - 1 - 2 3 4 4 4 46 Eastbound D2L12 ------4 4 4 2 3 - - - 2 3 4 2 3 4 1 - - - 36 Revenue Kitchener D1L6 1 - - - - - 1 1 1 1 4 4 4 3 1 1 2 2 2 3 4 4 4 3 46 Westbound D2L12 3 1 - - - - 2 3 3 3 - - - 1 3 4 4 4 3 1 - - - 1 36 Eastbound ------1 ------1 2 VIA Rail VIA D1 Westbound ------1 ------1 ------2 GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

APPENDIX D: Sample Calculation and Additional Details of Emission Rates for Local Air Quality Assessment

Revision DE 03-Dec-2020 Table D-1: Average GO Train Speed and Horsepower Assumptions for Study Segment [1] Distance from Direction Study Segment Segment Status Speed (km/hr) Notch BHP Strachan Ave (km) West of Malton West of Malton >21350 42 7 3,658 Station Westbound Station to East of East of Bramalea Bramalea Station >21560<22640 48 1 232 Station East of Bramalea >22320 47 1 232 Station East of Bramalea Eastbound Station to West of < 22320 "Middle Section" 58 6 2,878 Malton Station West of Malton < 21780 54 1 232 Station

[1] Averages from NAV analysis of speed and throttle profiles, shown in Appendix D of the Kitchener Corridor Noise and Vibration Study

Table D-2: Notch Setting and Corresponding Brake Horsepower for MP40 Locomotive [1] NOTCH L. Idle Idle DB [2] 1 2 3 4 5 6 7 8 BHP 9 28 47 232 449 983 1,445 1,876 2,878 3,658 4,230 [1] Data from an MP40PH-3C EMD 16-710G3C-T2 engine test on 12/11/07. [2] Dynamic Braking.

Table D-3: Speciation Factors from MOVES2014b Toxics Factor - Nonroad Diesel [1] Tier Acrolein Benzene Benzo(a)Pyrene Formaldehyde Acetaldehyde 1,3 Butadiene Tier 0 3.0E-02 2.0E-02 2.1E-06 2.1E-01 7.5E-02 1.9E-03 Tier 2 1.9E-02 5.4E-02 6.7E-06 2.9E-01 1.0E-01 1.9E-03 Tier 3 1.9E-02 5.4E-02 6.7E-06 2.9E-01 1.0E-01 1.9E-03 Tier 4 1.0E-02 5.4E-02 6.7E-06 2.9E-01 1.0E-01 1.9E-03 [1] "Speciation Profiles and Toxic Emission Factors for Non-Road in MOVES2014b", US EPA, p. 16

Table D-4. Locomotive Emission Factors Locomotive Emissions Emission Factors (g/bhp-hr) [1] [2] [2] [2] [2] [3] [4] [5] [5] [5] [5] [5] [5] Distribution Tier CO PM10 NOx HC VOC PM2.5 Acrolein Benzene Benzo(a)Pyrene Formaldehyde Acetaldehyde 1,3 Butadiene 8 Tier 0 5.0 0.2 8.0 1.0 1.05 0.21 3.2E-02 2.1E-02 4.7E-07 2.2E-01 7.9E-02 2.0E-03 56 Tier 2 1.5 0.2 5.5 0.3 0.32 0.19 5.9E-03 1.7E-02 1.3E-06 9.2E-02 3.3E-02 5.9E-04 10 Tier 3 1.5 0.1 5.5 0.3 0.32 0.10 5.9E-03 1.7E-02 6.7E-07 9.2E-02 3.3E-02 5.9E-04 17 Tier 4 1.5 0.03 1.3 0.14 0.15 0.029 1.5E-03 8.0E-03 2.0E-07 4.3E-02 1.5E-02 2.7E-04 Weighted Emission Factor 1.8 0.16 4.9 0.33 0.35 0.15 7.4E-03 1.6E-02 9.7E-07 9.4E-02 3.4E-02 6.5E-04 [1] As per email from Metrolinx, dated December 18, 2019

[2] "Control of Emissions of Air Pollution From Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Litres per Cylinder" 73 Federal Register 126 (30 June 2008), p. 37199 [3] 1.053 x HC [p.4 of "Emission Factors for Locomotives", U.S. EPA Office of Transportation and Air Quality, EPA-420-F-09-025, April 2009] [4] 0.97 x PM [p.4 of "Emission Factors for Locomotives", U.S. EPA Office of Transportation and Air Quality, EPA-420-F-09-025, April 2009] [5] "Speciation Profiles and Toxic Emission Factors for Non-Road in MOVES2014b", US EPA, p. 16, Table F-3 Table D-5. Head End Power (HEP) Unit Emission Factors Locomotive Horsepower Emissions Emission Factors (g/bhp-hr) [1] [8] Distribution Category Tier CO PM10 HC VOC NOx PM2.5 Acrolein Benzene Benzo(a)Pyrene Formaldehyde Acetaldehyde 1,3 Butadiene 8 - Tier 0 [2] 5.0 0.22 1.0 1.05 8 0.213 3.18E-02 2.06E-02 4.71E-07 2.18E-01 7.86E-02 1.96E-03 56 > 750 Tier 2 [3] 2.6 0.15 0.55 0.58 4.8 0.146 1.08E-02 3.13E-02 1.00E-06 1.69E-01 6.02E-02 1.08E-03 10 > 750 Tier 3 [3] 2.6 0.15 0.55 0.58 4.8 0.146 1.08E-02 3.13E-02 1.00E-06 1.69E-01 6.02E-02 1.08E-03 16 <= 1,200 Tier 4 [4] 1.5 0.03 0.14 0.15 1.3 0.029 1.47E-03 7.98E-03 2.00E-07 4.30E-02 1.53E-02 2.74E-04 1 <= 1,200 Tier 4 [5][7] 2.6 0.02 0.14 0.15 0.5 0.019 1.47E-03 7.98E-03 1.33E-07 4.30E-02 1.53E-02 2.74E-04 Weighted Emission Factor 2.6 0.13 0.51 0.54 4.4 0.13 1.1E-02 2.6E-02 8.0E-07 1.5E-01 5.3E-02 1.0E-03 [1] As per email from Metrolinx, dated December 18, 2019 [2] Tier 0 trains do not have a separate HEP Unit; emission factors are assumed to be the same as that of the locomotive [3] Tier 2 & Tier 3: "Control of Emissions of Air Pollution From Nonroad Diesel Engines" 63 Federal Register 205 (23 October 1998), p. 56970 [4] As per email from Metrolinx, dated December 18, 2019, 16 of the Tier 4 trains do not have separate HEP units; emission factors are assumed to be the same as that of the locomotive [5] As per email from Metrolinx, dated December 18, 2019, 1 of the Tier 4 trains has a separate HEP unit, and the Non-Road emission factors apply Tier 4: "Control of Emissions of Air Pollution From Nonroad Diesel Engines and Fuel" 69 Federal Register 124 (29 June 2004), p. 38980 [6]See Locomotive Emission Factors (Table F-3) for EF formula references [7] Tier 4 CO Emission Factor is based on previously applied Tier 2 standard; "Control of Emissions of Air Pollution From Nonroad Diesel Engines and Fuel" 69 Federal Register 124 (29 June 2004), p. 38971 [8] The Tier 2 and 3 non-road HC emission factors correspond to the Tier 1 locomotive HC emission factor. Reference document : "Control of Emissions of Air Pollution From Locomotive Engines and Marine Compression-Ignition Engines Less Than 30 Litres per Cylinder" 73 Federal Register 126 (30 June 2008), p. 37199

Sample calculation for emission rate of CO from a 15 meter x 15 meter volume source representing a mobile locomotive unit on a GO train operating at Notch 7 and travelling at 42 km/h:

Parameter Value Units Notes EF= 1.8 g/bhp-hr CO weighted emission factor per locomotive L= 15 m Length of source S= 42 km/hr Train travel speed BHP= 3658 bhp Brake horsepower N= 1 locomotives/hr # trains per hour travelling through volume source 3600= 3600 s/hr Conversion from hr to sec ER= 6.56E-01 g/s Pollutant emission rate

Emission Rate = Emission Factor x Length of Source / Train Travel Speed x Brake Horsepower x Number of trains per hour / 3600

Emission Rate = 1.8 g 15 m hour 3658 bhp 1 locomotive 1 hour = 6.56E-01 g/s bhp-hour source 42 km hour 3600 seconds GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

APPENDIX E: Emission Source Orientation in AERMOD

Revision DE 03-Dec-2020 608400 608500 608600 608700 608800 608900 609000 609100 609200 609300 609400 4840200 4840200 4840100 4840100 4840000 4840000 4839900 4839900

Legend 4839800 4839800 Volume Sources 0 100 200 300m

608400 608500 608600 608700 608800 608900 609000 609100 609200 609300 609400

Orientation of Volume Sources in AERMOD True North Drawn by:MFCFigure: E.1

[ Exact Scale: 1:5,000

Map Projection: NAD 1983 UTM Zone 17N Date Revised: Nov 25, 2020 Kitchener Corridor - GO Rail Network Electrification Project - Toronto, ON Project #: 1500999 M a p D o c u m e n t: C :\U s e rs \m fc \O n e D riv e - R W D I\D e s k to p \G IS \K IT _ F ig u re s \2 0 0 6 1 0 _ K IT _ F ig u re .a p rx GO Rail Network Electrification Project Air Quality Study –Kitchener Corridor

APPENDIX F: FREQUENCY CURVES FOR HOURLY NO2

Revision DE 03-Dec-2020 Receptor 1 100% 90% 80% 70% 60% 50% 40% 30%

Concnetration 20% 10% 40 60 80 100 120 140 160 Percent of Time Below a Given 1-Hour Concentration (µg/m3)

Future Baseline 2020 CAAQS 2025 CAAQS Receptor 2 100% 90% 80% 70% 60% 50% 40% 30%

Concnetration 20% 10% 40 60 80 100 120 140 160 Percent of Time Below a Given 1-Hour Concentration (µg/m3)

Future Baseline 2020 CAAQS 2025 CAAQS Receptor 3 100% 90% 80% 70% 60% 50% 40% 30%