This document summarizes a study that characterized the spatial variability of traffic-related air pollution at the neighborhood scale. The study had two main goals: 1) Examine differences between neighborhoods near and far from industrial facilities and highways. 2) Characterize local and background spatial differences for different land use emissions. Key findings included higher local and background pollution levels in neighborhoods near highways compared to far neighborhoods. Background levels were also higher near large-scale industries, while local differences depended on industry scale. The study provides insight into how local and background pollution levels vary spatially at the neighborhood level.

1. High-resolution Characterization of
the Spatial Variability of Traffic
Related Air Pollution Exposure at the
Neighbourhood Scale
Kerolyn Katrina Shairsingh, Cheol-Heon Jeong , Greg Evans
University of Toronto
ISES Conference
October 10, 2016

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Motivation
• While many studies explored city-scale variability, limited
research investigated neighbourhood-scale
• Enhance our understanding of emissions sources by
characterizing air pollution from traffic related and non-
traffic related sources
• Can be achieved by separating total concentrations into
time-series signals representing local and background
levels

3. 3
Goal of Study
1. Examine spatial variation between neighbourhoods near
(<500m) and far (>1000m) from industrial facilities and
highways
2. Characterize local and background spatial differences at
the neighbourhood-scale for different land use emissions
• A novel aspect of this study was that it provided insight
into the spatial variation of local and background levels at
the neighbourhood-scale

4. 4
High Resolution Air Pollutants
Total concentrations can be separated into
local and background levels using time-series
CO,
PM2.5
(10s)
BC,UFP
(1s)
NO, NOx
(20s)

5. 5
Separation of Local and Background Levels

6. 6
Time-Series Background Signal
Background
Signal
Regional-Scale
(>50km)
Synoptic
weather
Neighbourhood
Scale (<4km)
Vehicle Exhaust
(<1km)
Industrial Stack
(>1km)

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Example 1: Local and Background Levels
Influence of highway traffic on the background

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Example 2: Local and Background Levels
Influence of large-scale industry on the background

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Mobile Sampling Campaign
• Greater Toronto Area for seven (7) days in summer of
2015
• Neighbourhoods were selected based on different land-
use (industries, highways, commercial areas)
• Each route included neighbourhoods that represented the
regional background (parks or residential areas) for that
given location
• The area of neighbourhoods ranged in size from 2 – 6
sq.km

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Sample Route and Industries

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Neighbourhood Comparisons
• Near-highway vs Far-highway
Influence of highways on local and background levels
• Near-industry vs Far-industry
Impact of industry’s scale of operation on resolved levels

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Higher local & background levels in neighbourhood near the
highway
Near-highway neighbourhood had higher traffic volumes
Local Background

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Higher background & local levels in neighbourhood with
large-scale industries
Local Background

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Higher background levels in neighbourhood with medium-
scale industries
Dissimilar local and background spatial differences for neighbourhood near industries
Local Background

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Major Findings
• Near-highway local and background levels were greater
than far-highway neighbourhoods
• Near-industry background levels were higher than far-
industry neighbourhood, while local spatial differences
depended on industry’s scale of operation
• The disparity in spatial variability between local and
background levels for different land use emissions may
affect the performance of land-use regression models

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Thank You! Any Questions