fugitive emissions from a dry coal fly ash storage pile€¦ · stephanie l. shaw (epri), stephen...
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Stephanie L. Shaw (EPRI), Stephen F. Mueller, Qi Mao, Ray Valente, and John Mallard (Tennessee Valley Authority)
20th International EPA Emission Inventory Conference
August 13-16, 2012
Fugitive Emissions from a Dry Coal Fly Ash Storage Pile
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Why Are Fugitive Particulate Emissions Important?
• Upcoming coal ash storage regulation may rely on dry ash handling
• Potential impact to local communities
• EPA proposing to lower annual PM2.5 standard to 12 µg m-3.
• Detailed prevention of significant deterioration (PSD) analyses are required for a new/modified source when emissions for PM2.5 >10 tons per year (tpy), for PM10 >15 tpy and for TSP >25 tpy.
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Technical Motivation to Re-evaluate Fugitive Emissions
• Inaccurate fugitive emissions can lead to ineffective emissions control
• Fugitive EFs for fly ash highly uncertain – Ash handling, wind erosion or pile maintenance, transfer… – May not account for most important materials characteristics, site-
specific data, or current materials handling practices
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Overall Study Plan
• Phase 1: Dry fly ash– TVA Colbert Plant (AL) 1200MW • Phase 2: Coal dust – TVA Gallatin Plant (TN) 1000MW • Phase 3: TBD - Limestone/gypsum? Road dust? Fly ash in Western U.S.?
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Project Goals
• Quantify fugitive particulate emissions at coal-fired power plants for different handling practices.
• Compare new emission rates with those from EPA AP-42 handbook.
• Utilities use to inform facility permitting.
• May help evaluate emission mitigation strategies
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Origins of AP-42 Fugitive Emission Factors
• Studies in 1970s measured airborne dust near unpaved roads and material handling. Multi-component statistical analyses to develop formulations. Dropping factors -1980s
• Used old measurement technologies. • Most sources were staged & not done under actual
operating conditions. • Involved limited types of materials & limited range in
conditions (vehicle speed, material moisture content, silt content).
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bscat Ash handling
Dumping ≈25 m3 per load
Leveling to 0.5 m high x 4 m dia.
Grading time ≈8 min
Grader speed ≈5 mph
Loads per hr = ≤12
road dust
Study Concept
0 20 40 60
5 15
25
35
45
55
65
75
85
>90
%
Conc., µg/m3
PMc PM2.5
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Colbert Field Study Layout
Fly ash
disposal area
N
102 m
56 m
Potential
source
location
Photos:
(Top) Camera triggered by trucks moving along berm road south of air monitoring sites.
(Bottom) Camera triggered by activity on fly ash dry stack. 8 20 m high
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Monitoring Instrumentation
Instrument Measurement/Purpose Met One beta attenuation monitors (BAMs) at downwind & background sites
PM2.5/PM10 concentrations (semi-continuous) @ downwind & background sites
BGI PQ-200 PM10 particle filter sampler Filtered PM10 sample, ~12-hr samples (for chemical analysis) @ downwind & background sites
TSI 3563 3-λ nephelometer Continuous βscat @ 3 wavelengths @ downwind site
Optek nephelometer Semi-continuous single-wavelength βscat @ downwind site
Campbell Scientific video camera Semi-continuous images of fly ash disposal site
Instrument Measurement/Purpose R. M. Young 81000RE sonic anemometers (2 & 10 m)
Wind speed, direction, vertical velocity, horizontal & vertical turbulence; vertical gradient of speed, direction & turbulence
Vaisala HMI41 aspirated temperature & humidity sensors (2 & 10 m)
Air temperature & relative humidity; vertical temperature & moisture gradients
Campbell Scientific CNR2 net radiometer (~1.8 m) Radiation flux (shortwave, longwave & net)
Novalynx Corp. 260-2501-A tipping bucket raingage
Precipitation amount
Campbell Scientific CS616 water content reflectometer (top 30 cm of soil)
Soil moisture content
Met
eoro
logi
cal
Air
Qua
lity
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Dry Fly Ash Handling at Colbert
• Fly ash is pneumatically conveyed to hoppers where it is conditioned with 15% moisture before transference to haul trucks.
• Each truck moves 25-28 m3 of ash per load. • Ash is dropped at disposal area and leveled to a depth of
about half a meter (18-24 in). • Ash grading takes about 8 min with grader moving at 2.2
m s-1 (5 mph). • Fugitive emissions are primarily due to dropping and
grading operations (haul trucks moving over bottom ash road produces very little fugitive dust).
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Average Particulate Concentrations by Direction May-August 2011
One-hr average concentrations were measured by FRM BAMs and reported here in µg m-3.
Wind direction was measured at a height of 10 m.
(3) (2)
Data recovery >99%
Data recovery 81% Data recovery >99%
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Hourly Concentrations at each Site: May-September 2011
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Clean Period (No Emissions) 28 June, 1300-1400 LST
0
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06/2
8/20
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3:00
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11 1
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3:16
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11 1
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3:22
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3:24
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3:26
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3:28
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3:32
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3:34
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3:56
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11 1
3:58
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11 1
4:00
B_sc
at
20110628_13:00-14:00
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No-Vehicle Period (Fly Ash Activity only) 8 July, 1000-1200 LST
20
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07/0
8/20
11 1
0:00
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0:06
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11 1
0:09
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0:12
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0:18
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B_sc
at
20110708_10:00-12:00
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3-Vehicle Event 22 July, 0700-0800 LST
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07/2
2/20
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:00
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:00
B_sc
at
20110722_07:00-08:00
1 2
3
All three dust spikes were caused by dump trucks on the berm road.
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Particle Concentrations (SSE-SSW)
y = 0.225x + 1.854 R² = 0.770
0
10
20
30
40
0 20 40 60 80 100 120 140
µg m
-3
Mm-1
PM2.5 Concentration vs. bscat
y = -0.014x2 + 6.432x - 2.745 R² = 0.725
1
10
100
1000
0 10 20 30 40 50 60 70
µg m
-3
Mm-1
PMc Conc. vs. σbscat
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Models of Hourly PMc & PM2.5
Ccoarse=fσσbscat + fU2U2 + ffineCfine + Cint r2=0.77
Multivariate linear regression yields
Cfine=fbscatbscat + fU2U2 + Cint r2=0.89
f : regression slope constants
bscat : light scattering coefficient (Mm-1)
σscat : standard deviation of bscat (Mm-1)
U2 : wind speed at level 2 (m s-1 @10 m)
Cint : intercept constants (µg m-3)
Cfine : concentration of PM2.5 mass (µg m-3)
Ccoarse : concentration of PMc mass (µg m-3)
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Steps in Estimating Fly Ash Emission Rates
18
Select hours meeting minimum data requirements
Calculate “adjusted” concentrations at sites 2 & 3 to remove effects of nearby emissions
Calculate “excess” concentrations (i.e., values above background), Cxs
Compute normalized concentrations (C/Q)
Compute Qi=Cxsi/(C/Q)
For each particle size:
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Fly Ash Emission Equations
Based on AP-42: Eash= Nloads (Edrop + DEgrad / m)
Nloads = ash loads per unit time D = grader distance traveled per load processed m = ash mass per load
Based on field data & modeling:
Cxsobs = Cobs - Clocal – Cbck
Qash = Cxsobs /(C/Q)model
Eash = Qash /Mash Mash = ash mass deposited per area per time
grading
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Overall Emission Factors
g particles/ metric ton of processed ash
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Estimating Vehicle Dust Emissions
Assuming an infinite line source and a Gaussian plume mass profile, calculate an emission rate of mass per unit length of road per unit time as (following Hanna et al., 1982)
Qi=2.46Ci (Kux)½ exp[uz2/(4Kz)]
where Ci is observed concentration of mass component i, u is wind speed, x is downwind distance, K is eddy diffusivity, and z is the vertical height displacement from the plume centerline (z=0 for a ground level source). Near the ground under steady-state conditions, K can be determined using the relation
u*2=K(du/dz)
with both u* and du/dz known from measurements at the nearby meteorological tower.
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Emission Factor Summaries
Emission Factor Coarse Mass, PMc Fine Mass, PM2.5 Mean Median Mean Median
Fly Ash, AP-42 (g PM per Mg ash) 250 232 45 41
Fly Ash, this study (g PM per Mg ash) 63 12 14-18 5-7
Road dust, AP-42 - industrial sfc. (g PM per km traveled) 193 200 34 36
Road dust, AP-42 - public roads (g PM per km traveled) 32 26 5.7 4.6
Road dust, this study (g PM per km traveled) 68e 38e 3.3 1.4
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What controls total ash disposal EFs?
• Grading activity accounts for >95 percent of total computed fugitive fly ash emissions.
• AP-42 grading EF formulation is for vehicles on industrial roads but was developed from surfaces relatively low (<25%) in silt content, no moisture, higher speeds.
• Tested both AP-42 unpaved road dust formulations at Colbert on 2 roads/42 events.
• Results*: Industrial AP-42 EF 10x observed for PMc Industrial AP-42 EF 23x observed for PM2.5 Public road AP-42 EF 2x observed for PMc Public road AP-42 EF 4x observed for PM2.5
*Differences between AP-42 and field results are even larger when vehicle wake effects are considered.
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Conclusions • Despite conservative assumptions, AP-42 derived fly ash handling EFs are higher
than EFs derived by field measurements for both PMc and PM2.5 • Disparity is likely due to high bias in industrial unpaved road dust formulation
(grading).
• EFs from field measurements have higher tail than AP-42 EFs. May be due to higher variability in atmospheric or ash handling conditions in real operations.
• Use of more realistic EFs can lower fugitive dust emission estimates for fly ash handling by 33% (PM2.5) to 80% (PM10). Can benefits be expanded to TSP?
• Observed EFs for vehicles on unpaved roads also differ from AP-42 EFs.
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