Air Pollution in Hamilton – Health Effects and Sources November 22, 2006 McMaster Centre for Spatial Analysis

Clean Air Hamilton Strategy Risk Management Approach Applied to Community Wide Actions Identify Problem Measure/Evaluate Prioritize Risks Inform Community Cooperative Actions

The Problem Sahsuvaroglu & Jerrett 2003 Health Impacts of Air Pollutants in Hamilton

Health Impacts in Hamilton – by Air Pollutant Sahsuvaroglu & Jerrett 2003

Study Objectives, Phase 1 “Where is it coming from?”  Identify and rank sources, including transportation sources, of NOx, SO 2, Airborne Particles and CO, using mobile monitoring techniques (no direct local sources of Ozone).  Investigate the effect of idling vehicles at a designated school during student drop off and pickup times.  Investigate trackout/road dust issues

National Pollutant Release Inventory – Hamilton Point Sources PM Sources CO14 Sources NO x 13 Sources SO 2 9 Sources

Total Point Source Emissions by Contaminant COSO x NO x PM 10 30,63211,8758,1882,010 Tonnes

What We’d Expect to See Carbon Monoxide – 66% Transportation, 23% Industry Sulphur Dioxide – 92% Industry, 5% Transportation Nitrogen Oxides – 57% Transportation, 37% Industry PM 10 – 73% Open Sources/Road Dust, 18% Industry Note: MOE identified trackout/road dust resuspension as a major problem

Emission Sources by Regions in Hamilton Flamborough/ Waterdown East Mtn NE Ind Stny Crk

Mobile Command Centre

Instrument Rack Mounts

A/D Converter, Data Logger, GIS Software

Roof Mounting Sampling Intakes Gaseous/Particulate

GPS Head, Garmin 18, GIS Display

City/Traffic Monitoring 1.City Wide Sampling 2.Road Dust/Road Impacts 3.Intersection Impacts 4.Arterial Road Impact/ Burlington St. 5.Cycle Routes/ Anti Idling

Sampling Track, City Wide Scan

City Wide Sampling

Wind NO ppb

Wind

City Wide Sampling, Residential Locations

Roads vs Residential Areas

Stoplight Idling – Concentrations Downwind

Burlington St. Upwind Downwind

Burlington St Contribution (Approx. 600 Trucks/Hr)

CARS

Vehicle Idling outside Schools “Natural Experiment”

Natural Experiment ppb

Morning – Idling Vehicles

Trackout/Diesel Trucks 1.PM 2.5, PM 1 Components 2.Photos 3.Sample Trace 4.Consolidated PM 10 Data 5.Comparison Previous Data

Road Dust, Covariance 20xPM 1, 10xPM 2.5, PM 10

Road Dust/Trackout 18 Locations Monitored, 14 Sources Identified

PM10 ROAD DUST Ben Garden, Savas Kanaroglou, Pat DeLuca, Spatial analysis Unit, McMaster University

Source Tracking 1.Photos 2.SO 2 Tracing 3.Other Contaminants 4.SO 2 Data Consolidation 5.Source Ranking/NPRI Comparison, SO 2, NO, PM 10

B Sources B

Source AY

All Scans 21 March

SO 2 Company A

Source Plume Back Tracking Impact Source

SO 2 Company A

NO Company A

19 Jan SO 2

Ambient SO 2 vs NPRI SO 2 Point Sources: A-Integrated Steel, B-Integrated Steel, AN- Steel Byproducts, C- Carbon Black, G-Steel, B-Integrated Steel, A-Integrated Steel, D-Lime, CP-Rail Yard.

Ambient NO vs NPRI NO Point Sources: B-Integrated Steel, CP-Rail Yard, G-Steel, A-Integrated Steel, AN- Steel Byproducts, D-Lime, C-Carbon Black, AM-Cogeneration, AT-Chemical.

Ambient PM 10 vs NPRI PM 10 Point Sources: B-Integrated Steel, ABP-Recycling, AY-Agricultural Product Handling, AG- Aggregate or AZ-Steel Handling, AU-Recycling, AT-Chemical, M-Foundry, G-Steel, CP-Rail Yard, A- Integrated Steel, AM-Natural Gas Cogeneration Facility, C-Carbon Black.

Ambient CO vs NPRI CO Point Sources: AM-Cogeneration, AT-Chemical; AN- Steel Byproducts; B- Integrated Steel; A-Integrated Steel; G-Steel; C-Carbon Black; CP-Rail Yard.

Continuous Monitoring Locations Centre Industrial

SO2

NE

Conclusions These data are limited to Winter season and for relatively short periods of time. Point sources in the industrial area are sufficiently close together that specific compounds needed to be used as tracers to separate impacts. Residential areas have relatively low levels of pollutants, however city impacts increase as distance downwind from the city edge increases. Concentrations increase sharply from residential areas to main roads, increasing again at intersections. Peak concentrations may increase by factors of Time pattern of concentrations near intersections shows that idling vehicles at stop lights are a very significant source of pollutant exposure. Short survey near a school pickup and drop-off point showed that air pollution concentrations experienced by students can be significantly reduced by turning off engines in waiting cars.

Conclusions (contd) Road dust includes elevated PM 10, PM 2.5 and PM 1. Trackout resuspension by large diesel trucks is a major problem. Some levels doubled from same period in previous year. 14 severe Trackout locations identified and monitored. Peak ambient values of NO, SO 2, PM 10 and CO from 15 point sources were quantified and ranked. NPRI data rank industrial emissions in Hamilton in the order CO, SO 2, NO and PM 10, and total emissions in the order CO, PM 10, NO, SO 2. Mobile monitoring to date is showing an order of CO, PM 10, NO, SO 2, even in the industrial area. Large differences in distance from point source to fencelines heavily modify direct impacts compared to NPRI emissions data. Even allowing for distance variations there are significant differences between ambient and NPRI data for some sources. Other sources show good agreement. Mobile monitoring has different strengths than fixed network monitoring and both are necessary. Combination of simple GIS analysis and air pollutant monitoring proved very useful. A more sophisticated GIS analysis would be worthwhile. Data can be used to refine Regulation 419 models

Recommendations Move cycle lanes off main roads, innovative signage. Reduce idling emissions, including at school dropoff locations (enlist parent teacher groups). Monitor school bus idling. Prioritize trackout reduction - paving, wheel washing, front gate dust monitoring. Reinstate/enhance targeted road cleaning in industrial areas. Reduce large diesel truck trips, it’s the combination of heavy trucks and dirty roads that is a problem. Gateway monitoring of diesel exhaust at city entry/exit points, industrial arterials. Continue reducing point source remissions of SOx, NOx and PM 10 (both ambient and NPRI data) in order to improve/reduce health impacts. Review existing fixed network stations and locations to refocus on adverse health causing pollutants, e.g. NOx, monitoring gaps. Compare mobile data to MOE STAC data, more detailed GIS analysis. Review NPRI data variances with ambient. Extend mobile monitoring to other seasons for more definitive source separation in complex areas and documenting different met regime impacts, particularly inversions. Extend mobile monitoring to other communities. Use mobile data to refine local source inputs to Regulation 419 models. Disclaimer:- All recommendations and opinions are the sole responsibility of D. Corr and do not necessarily represent the policy or position of funding agencies or others.

Phase 2 Proposal Perform a more sophisticated and comprehensive GIS analysis of existing data to develop traffic impact and source impact mapping visualization Re equip instrumentation and modify the data collection system in the Mobile Unit for consolidated air pollution/GPS data collection. Meet with stakeholders to finalize monitoring targets and locations. Support the MOE and City of Hamilton Fugitive Emission Control Initiative through monitoring of control activities for effectiveness. Test existing models of city wide distribution of air pollution and extend mobile monitoring to fill data gaps across the City, e.g. Dundas, Stoney Creek. Perform Smog day/Inversion day monitoring, upwind of City and across City to identify Regional and Transboundary impacts and compare to City impacts.

Phase 2 Proposal Perform sampling on major arterial roads, at intersections and drive thrus. Monitor downwind impacts of roads and intersections on residential areas. Perform more intensive monitoring of NPRI and other point sources identified in Phase 1 in consultation with MOE staff. Utilize McMaster University advanced spatial analysis capabilities for pollution source visualization and in depth data analyses. Provide monitoring data to modelling initiatives for ongoing model calibration, e.g., GTA/Hamilton modelling exercise (Phase 2. Generate recommendations for air quality improvements. Develop and give presentations on findings and recommendations.