trends in inter- and intraurban ultrafine particle levels ......• toronto – greg evans • la...
TRANSCRIPT
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Trends in Inter- and Intraurban Ultrafine Particle Levels in the U.S.: Exposure Implications
Albert PrestoDept. of Mechanical Engineering
Center for Atmospheric Particle Studies
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Important questions about UFP exposures• Concentrations and spatial/temporal trends
• What are typical concentrations?• What are the trends over time?• What are the inter- and intra-city spatial patterns?
• UFP sources• What are the major sources, and how do they drive temporal and spatial
patterns?• What are contributions of primary and secondary particles?
• UFP exposures• What is the current ability to estimate exposures?• What would be needed to improve exposure estimates?
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Reminder 1: There is not a regulatory standard for UFP measurement or quantification
This presentation will use particle number count (PNC, # cm-3) as a UFP surrogate
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Reminder 2: UFPs are a data-poor pollutant
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This is the current EPA network for PM2.5
Source: US EPA
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This is the current EPA UFP network
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We will investigate trends with a small number of cities that have long(er) term measurements
Toronto Rochester
BostonPittsburgh
Rural OK
Bay Area (2)
Los Angeles (4)
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PNC concentrations have fallen ~30% since 2006
PNC average of 4 cities: Boston, Rochester, Toronto, Rural OK
PNC
(cm
-3)
Norm
alized to 2006
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PNC concentrations have fallen ~30% since 2006
PNC average of 4 cities: Boston, Rochester, Toronto, Rural OK
National PM2.5reduction of 35% since 2006
PNC
(cm
-3)
Norm
alized to 2006
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PNC concentrations are highly variable
Rur
al O
K
Ratio to R
ural OK
Ratio to rural OK
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PNC range from <5,000 to >20,000 cm-3
Rur
al O
K
Ratio to R
ural OK
Ratio to rural OK
PNC
(cm
-3)
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PNC concentrations are highly variable and depend on sampling location
Rur
al O
K
Ratio to R
ural OK
Ratio to rural OK
PNC
(cm
-3)
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How much of this inter-city variation is a result of the specifics of each sampling site?
Rur
al O
K
Ratio to R
ural OK
Ratio to rural OK
PNC
(cm
-3)
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PNC varies by a factor of 2-3 at urban scales
Saha et al, STOTEN, 2019
PNC
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We investigated inter- and intra-city PNC with mobile sampling
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We investigated inter- and intra-city PNC with mobile sampling
30 x103
25
20
15
10
5
0
PNC
(#/c
c)
3210
Oakland Baltimore Pittsburgh Pittsburgh(Stationary)
(Mob: 15d+)N = 330
(Mob: 5d+)N = 144
(Mob: 5d+)N = 207
N = 30
Oakland Baltimore Pittsburgh
PNC
(cm
-3)
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We investigated inter- and intra-city PNC with mobile sampling
30 x103
25
20
15
10
5
0
PNC
(#/c
c)
3210
Oakland Baltimore Pittsburgh Pittsburgh(Stationary)
(Mob: 15d+)N = 330
(Mob: 5d+)N = 144
(Mob: 5d+)N = 207
N = 30
Oakland Baltimore Pittsburgh
PNC
(cm
-3)
Intra-city variations are a factor of 2-3
Inter-city variations are also a factor of ~2
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Inter- and intra-city PNC variations are larger than for PM2.5
Saha et al, STOTEN, 2019
PNC
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Inter- and intra-city PNC variations are larger than for PM2.5
Saha et al, STOTEN, 2019
PNC PM2.5
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PM2.5 variability is much smaller and concentrations are less dependent on sampling site
Rur
al O
K
Ratio to R
ural OK
PNC
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PM2.5 variability is much smaller and concentrations are less dependent on sampling site
Rur
al O
K
Ratio to R
ural OK
Rur
al O
K
Ratio to R
ural OK
PNC PM2.5
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Summary: Concentrations and trends• Typical concentrations: <5k to >20k cm-3. Urban ~10k cm-3
• Trends over time: 30% decrease since 2006• Inter- and intra-city spatial patterns: Factor of 2 within and
between cities
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Traffic and nucleation are two major sources
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Traffic: Large reductions in near-road PNC over time
20,000 cm-3
Nea
r Roa
d PN
C (c
m-3
)
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Nucleation: Often driven by SO2 chemistry
Saha et al, ES&T, 2018
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Nucleation: Fallen by half since 2002
Saha et al, ES&T, 2018
% o
f nuc
leat
ion
days
Pittsburgh
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Nucleation: Fallen by half since 2002
Saha et al, ES&T, 2018
% o
f nuc
leat
ion
days
SO2 emissions
Pittsburgh
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Summary: Sources• Major sources: Traffic and nucleation• Contributions of primary and secondary particles: Much of the
urban enhancement is primary.
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What is the status of exposure assessment for epidemiology?
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Recall: This is the current EPA UFP network
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Exposure assessment generally relies on single-city LURs built from mobile or distributed sampling
Saha et al, ES&T, 2019
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Widescale UFP sampling can be expensive and time consuming
Many studies have used short-term or quasi-stationary sampling to fill data gaps
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Exposure estimates based on short-term monitoring can partially fill the data gap
R2
Short-term monitoring
Saha et al, ES&T, 2019
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There is large improvement with modest additional sampling
R2
Short-term monitoring
Saha et al, ES&T, 2019
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We are a long way off from national estimates
Saha et al, ES&T, 2019van Donkelaar et al, EST, 2015
PM2.5: continental-scale estimates that combine satellite and ground data
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What is needed to improve UFP epidemiology?
• More data is needed in more locations• Systematically and continuously collected• 10s of sites per city in a mix of rural, suburban, and urban locations
• National-scale exposure estimates are not currently possible• Require either a large investment in monitoring or improvement in
chemical transport models
• Improved UFP exposure and epidemiology data are likely necessary to help drive policy changes
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Acknowledgments
• Center for Air, Climate, and Energy Solutions (CACES)• U.S. Environmental Protection Agency, Assistance Agreement No.
RD83587301• Data access
• Boston – Harvard (Petros Koutrakis; US EPA grants (RD-835872 and RD-834798))
• Rochester – Phil Hopke• Toronto – Greg Evans• LA and Bay Area – Public records from SCAQMD and BAAQMD• Southern Great Plains – US DOE
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PNC concentrations at a given location depend strongly on site characteristics. This is less of an issue for PM2.5.
Intra-city variations are large for PNC
Robust exposure estimates require wide-scale distributed data collection
The large intra-city variations can mask inter-city variations
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Adapted from Lenschow et al, 2001