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Highly-Resolved Emissions and Concentrations of Pollutants in Salt Lake City, Utah for Air Quality and Health Daniel Mendoza, John Lin, Logan Mitchell, Martin Buchert, Amanda Smith, Ben Fasoli, Ryan Bares, Derek Mallia, John Horel, Erik Crosman, Sebastian Hoch, Douglas Catharine, James Ehleringer, University of Utah Kevin Gurney, Risa Patarasuk, Darragh O’Keeffe, Terry Song, Jianhua Huang, Arizona State University Denitza Blagev, Jeff Sorensen, Susan Rea, Intermountain Healthcare Measurements, Modeling, and Data Integration for Air Quality and Health September 21 st , 2016

Highly-Resolved Emissions and Concentrations of Pollutants in … · 2016. 9. 21. · 10 15 20 1 3 5 7 9 11 13 15 17 19 21 23 / hr) Hour Murray (6km x 6km) 0 10 20 30 40 50 60 1 3

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Page 1: Highly-Resolved Emissions and Concentrations of Pollutants in … · 2016. 9. 21. · 10 15 20 1 3 5 7 9 11 13 15 17 19 21 23 / hr) Hour Murray (6km x 6km) 0 10 20 30 40 50 60 1 3

Highly-Resolved Emissions and Concentrations of Pollutants in Salt Lake

City, Utah for Air Quality and Health

Daniel Mendoza, John Lin, Logan Mitchell, Martin Buchert, Amanda Smith, Ben Fasoli, Ryan Bares, Derek Mallia, John Horel, Erik Crosman, Sebastian Hoch, Douglas Catharine,

James Ehleringer, University of Utah

Kevin Gurney, Risa Patarasuk, Darragh O’Keeffe, Terry Song, Jianhua Huang, Arizona State University

Denitza Blagev, Jeff Sorensen, Susan Rea, Intermountain Healthcare

Measurements, Modeling, and Data Integration for Air Quality and Health September 21st, 2016

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Background

• Growing urban population in Salt Lake Valley

• Association between pollution and health

• Understudied intermountain region

• Urban valley conducive to inversions

• Multiple data streams available

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Salt Lake Valley Inversion

windows2universe.org

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What is Hestia?

• Highly resolved urban emissions data product – CO2 and selected Criteria Air Pollutants (CO, NOX, PM2.5) – Hourly resolution for 2010-2015 – Building, road segment, point source and gridded scales (0.002

deg ~ 200 m)

• Well-constrained – Bound by sector-specific fuel sales – CAPs derived from National Emissions Inventory

• Reliable and relevant data sources – County assessor data – Department of transportation and federal highway

administration – National Emissions Inventory

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Why CO2?

• Well understood

• Stable

• Multiple data streams

BUT…

• Vegetation contributions

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On

road

Re

sid

en

tial

C

om

me

rcia

l

2012 Salt Lake City Emissions (kg C/yr)

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Variability in Winter CO2 Emissions

0

10

20

30

40

50

60

1 3 5 7 9 11 13 15 17 19 21 23

Emis

sio

ns

(to

n C

/hr)

Hour

Salt Lake County

09/21/2016

Commercial Residential Onroad Total

7

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0

10

20

30

40

50

60

1 3 5 7 9 11 13 15 17 19 21 23

Emis

sio

ns

(to

n C

/hr)

Hour

Salt Lake County

09/21/2016

Commercial Residential Onroad Total

8

Variability in Winter CO2 Emissions

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0

5

10

15

20

1 3 5 7 9 11 13 15 17 19 21 23

Emis

sio

ns

(to

n C

/hr)

Hour

Murray (6km x 6km)

0

10

20

30

40

50

60

1 3 5 7 9 11 13 15 17 19 21 23

Emis

sio

ns

(to

n C

/hr)

Hour

Salt Lake County

09/21/2016

Commercial Residential Onroad Total

9

Variability in Winter CO2 Emissions

0

5

10

15

20

25

1 3 5 7 9 11 13 15 17 19 21 23

Emis

sio

ns

(to

n C

/hr)

Hour

University (6km x 6km)

Commercial Onroad

Total

Residential

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10 09/21/2016

Winter Sector Specific CO2 Emissions

log10

5 4 3 2 1 0

log10

5 4 3 2 1 0

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Annual Trends in Stationary CO2 Measurements

11

co2.utah.edu

Office of Science (BER), U.S. Department of Energy, grants DEFG0206ER64309, DESC0005266 09/21/2016

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Agreement with Observations

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Scale and Scenario Effects

Scale Matters! Sector comparison

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[CO2] above background, ppm

Morning in the Salt Lake Valley CO2

Transect: January 2013 Inversion

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TRAX Results: Monthly Average CO2

• High concentrations in downtown and University areas

• High concentrations at intersections with large roads

• Low concentrations at Daybreak and due to City Creek clean air influx

• Spatially correlated with high population and low elevation

Mitchell et al. - TRAX Pilot Project Results 09/21/2016 15

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Socioeconomic Attributes vs. Emissions

Percent Minority

0 - 6

7 - 14

15 - 25

26 - 43

44 - 100

Household Income (2011 Dollars)

8942 - 45162

45163 - 66346

66347 - 92118

92119 - 139886

139887 - 210750

Monitoring Sites

^

Acetaldehyde (lbs/yr)

0 - 33

34 - 147

148 - 390

391 - 1332

1333 - 2902

Benzene (lbs/yr)

0 - 73

74 - 293

294 - 680

681 - 1300

1301 - 3000

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Valley Wide Differences

ASB (University of Utah) Rose Park

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Pilot COPD study

• 90 patients (> 65 y/o, ~30% never smoked)

• Use highly resolved emissions to estimate hourly CO2 levels at each patient address

• CO2 levels for Dec 1, 2013 to February 28, 2014

• Clear spatial and temporal CO2 gradients for each patient residence

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Map of Individual CO2 Concentrations

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Individual hourly CO2 time series

CO

2 c

on

cen

trat

ion

g/m

3)

09/21/2016 Red Air Days

COPD Exacerbation

Patient 1

20

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CO

2 c

on

cen

trat

ion

g/m

3)

Median CO2 Concentration, First COPD exacerbation, and “Red Air” Days

09/21/2016 Red Air Days

COPD Exacerbations

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Distribution of CO2 Concentration: overall vs. 1-week prior to COPD exacerbation

Patient Average CO2 concentration (µg/m3)

Den

sity

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09/21/2016 23

Collect current UTA ridership information Analyze individual trips by purpose, air quality

Quantify transportation emissions due to transit behavior

Reduced fares on red air days

http://alg.umbc.edu/usaq/archives/2010_01.html

Estimate system-wide costs of transit behavior

The Effect of Air Quality on Transit Ridership Patterns and Associated Vehicle Emissions

Card ID Trip Purpose Air Quality

000001 Commute Red

000001 Non-commute Red

000002 Commute Orange

Direct and indirect emissions changes Air Quality Effects

CO CO2

NOX

PM2.5

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(gal) (g CO2) (g PM2.5)

log10

3 6 1.5

2 4 1

1 2 0.5 0

November 2015 Weekday Reductions TRAX

03/28/2016 09/21/2016 24

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Conclusions Unique sector-specific emission patterns have

been modelled:

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Elevated CO2 concentrations have been associated with COPD events:

Highly-resolved emissions are necessary for exposure estimation

and urban planning:

Modeled CO2 concentrations have been shown to agree with observations:

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Thank you!

Questions?

26 09/21/2016