awma 2016 critical review: emissions from oil and gas...
TRANSCRIPT
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David AllenDepartment of Chemical Engineering,
and Center for Energy and Environmental ResourcesUniversity of Texas at Austin
AWMA 2016 Critical Review:Emissions from oil and gas operations
in the United States and their air quality implications
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What have we learned from 15 years of VOC, NOx and GHG emission
studies along the oil and gas supply chains?
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Multiple approaches for measurement (bottom‐up and top‐down)
• Direct measurements of sources
• Fixed ground measurement network
• Mobile ground monitoring
• Aircraft monitoring• Satellite measurements• Different approaches
provide complementary information
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What do the measurements tell us?
• Spatial variability in emissions
• Temporal variability in emissions
• Super‐emitting sub‐populations
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Spatial variability in emission magnitudes by equipment or operation type
Spatial variability in emissions per pneumatic controller
Spatial variability in emissions due to liquid unloadings
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Spatial variability in emission compositions within production basinsBarnett Shale (Texas) ethane and propane to methane ratios
Oklahoma % VOCs in produced gas
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Spatial variability in the nature of emissions between regions and on scales as small as a few kilometers
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Temporal variability of emissions on multiple time scales, from minutes to years
• Changes in equipment on site and in reservoir characteristics as wells age
• Shorter term emission variability associated with planned episodic emissions – Start‐ups– Shutdowns– Blowdowns, separator dumps– Pneumatic controllers– Liquid unloadings
• Unplanned emission events
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What do the measurements tell us?
• Recent reviews by Miller, et al (2013) and Brandt, et al. (2014) conclude that top‐down data indicate methane emissions are higher than current bottom‐up estimates (a 50% increase over current bottom‐up anthropogenic emissions from all sources)
• Geographical variability
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Synthesis
• Emissions have significant spatial and temporal variability
• Magnitudes of activity and emissions are changing
• Some bottom‐up and top down approaches lead to different assessments of emission magnitudes
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Super‐emitters
A general finding emerging from many studies of the emissions from
oil and gas supply chains
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What is a super‐emitter?
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What is a super‐emitter?
• 10% of the passenger vehicle fleet on the road generates approximately 50% of total passenger vehicle emissions
• Super‐emitters caused by age, modifications, and equipment malfunction
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Super‐emitters in the oil and natural gas supply chains: Methane emissions
• New findings that sub‐populations of sources methane emissions along the natural gas supply chain (super‐emitters) dominate emissions in many source categories
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Super‐emitters in the oil and natural gas supply chains
• 2% of sites in the Barnett shale lead to >50% of the emissions
• 19% of pneumatic controllers lead to 95% of emissions
• 3‐5% of wells with liquid unloadingsaccount for more than half of emissions……..
1% of annual natural gas supply chain emissions from one large leak at a storage facility near Los Angeles (equivalent to >10,000 wells in routine operation)
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Case study of a super‐emitting sub‐population: Liquid unloadings (wells without plunger lifts)
0%
10%
20%
30%
40%
50%
60%
70%
<1 1 to 10 10 to 100 100 to 1,000 1,000 to5,000
5,000 to10,000
> 10,000
Percen
t of S
ample
Annual Methane Emissions Range (MSCF/yr)
Wells without Plunger Lift (32 total)Sampled Emissions Sampled Wells
Numbers of devices in various emission bins are well distributed about a mean value, but distribution of emissions is dominated by
high emitting sub‐population
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Super‐emitters in the oil and natural gas supply chains
• Super‐emitters and emission events known to occur (batch or episodic processing, upsets, periodic maintenance, blowdowns, process start‐ups, process shut‐downs) but have been poorly quantified
• First detailed analyses of super‐emitters in the oil and gas supply chain done for downstream processing in Houston
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Texas Air Quality Study (TEXAQS ‐ 2000)Provide scientific basis for air quality management strategies in
southeast Texas
(www.utexas.edu/research/ceer/texaqs/) (www.utexas.edu/research/ceer/texaqsarchive)
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Emission events (episodic super‐emitters) in Houston cause transient ozone events
Houston Dallas‐Fort Worth
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Evolution of Houston ozone spike
Wind
Industrial source region
Ozone plume
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TexAQS addresses key areas of uncertainty
• Chemical and physical processes in the atmosphere, particularly those leading to rapid and efficient ozone formation (a.k.a. ozone “spikes”)
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TexAQS data played a crucial role in understanding these events
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TexAQS addresses key areas of uncertainty
• Chemical and physical processes dominated by highly reactive volatile organic compounds (light olefins) that were being emitted in much greater quantities than expected
• This led to a search for missing emissions
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The missing emissions• Findings from TexAQSbegan the search for missing emissions
• They were found in barges, tanks, loading and off‐loading, flares, emission events,…….
• New technologies were demonstrated that made finding the emissions possible
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Super‐emitters: Continuous or episodic emissions?
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Self reporting of process emissions
• Based on findings on emission variability, new emission event reporting required beginning in 2003
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Harris, Galveston, Chambers, and Brazoria CountiesVOC Event Emissions
as Reported Jan 31 - Dec 31, 2003
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
0 730 1460 2190 2920 3650 4380 5110 5840 6570 7300 8030 8760
Yearly Hour
Emis
sion
s (lb
s/hr
)
Event Emissions
2001 Annual Avg
10,359 lbs/hr
Jan 1 Dec 31
64,860 lbs/hr
53,983 lbs/hr
86,557 lbs/hr
64,539 lbs/hr
Total Event Emissions = 4,035,322 lbs
• Total mass of over 4 million pounds (2000 tons) contributes 4% to the 45,000 tons of VOC emitted over a single year from point sources in the four counties.
• 14 times (18 hours) during the eleven‐month period, event emissions exceed the annual average for all facilities in the region.
VOCs4,000,000 lb
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What are the characteristics of the events in terms of time, space, and composition?
All HRVOC Eventsas Reported Jan 31 - Dec 31, 2003
0
100
200
300
400
500
600
0-24 24-48 48-72 72-96 96-120 120-144 144-168 >168
Event Duration (Hours)
Num
ber o
f Rep
orte
d Ev
ents
Unscheduled
Scheduled
Most events last less than a day, many last less than an hour
Largest number of events is from events of 100-1000 lb, but most of the mass is associated with events greater than 1000 lb, which occur, on average, several times per week
As Reported Jan 31 - Dec 31, 2003
160
375
142
331
0
100
200
300
400
500
0-100 100-1000 1,000-10,000 10,000-100,000 >100,000
Mass of HRVOC per Event (lbs)N
umbe
r of E
vent
s
Frequency of HRVOC events by HRVOC mass
2-3 times per week
DailyLess than 24 hours
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Conceptual issue
In most of US, industrial emissions are relatively constant or are small enough that meteorology is cause of “worst conditions” In Houston, both meteorology and emissions are cause of “worst conditions”
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An album of emission snapshots
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An emission snapshot for a sub‐region
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How do we reduce emissions?Case study of flares
• Flares have narrow operating windows to achieve both high combustion and low soot
• Full scale field studies to define those operating windows and then train operators
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Mitigating the impact of super‐emitters:Improvements 2000‐2006
Data from NOAA
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Applying these approaches to the Eagle Ford
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Quantify the emissions from the Eagle Ford
• While emissions of volatile organic compounds are the largest in quantity, they are relatively unreactive, and in the Eagle Ford occur in a region with high emissions of biogenics
• Ozone formation in the Eagle Ford is due almost exclusively to NOx
NOx VOC CO
Eag
le F
ord
Bas
e C
ase
Em
issi
ons
Inve
ntor
y (tp
d)
050
100
150
200
250
300
350
ExplorationPad ConstructionDrillingHydraulic FracturingWell CompletionRoutine ProductionMidstream
050
100
150
200
250
300
350
ExplorationPad ConstructionDrillingHydraulic FracturingWell CompletionRoutine ProductionMidstream
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Where the emissions occur also matters
NOx emissions that impact San Antonio NOx emissions that impact Austin
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What is the magnitude of the impact?
• Magnitude of impact approximately 1 ppb in Austin and San Antonio, depending on day and location; effects are likely to be stochastic
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Summary(Findings)
• How we address emissions along oil and gas supply chains is one of the most significant issues at the intersection of energy and air quality for the nation and the world
• Air emissions in the oil and gas supply chain are changing and have complex spatial and temporal variability
• Addressing super-emitters is a significant part of this challenge
• Experience over the past decade provides information about what will and will not work
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Recommendations
• Quantifying super‐emitters
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How can we develop emission inventories accounting for super‐emitters?
EFi, super-emitter * (f) AFi,
+ EFi, non-super-emitter * (1-f) AFi, = ERi
EFi, super-emitter = Emission Factor for super-emitters in region iEFi, non-super-emitter = Emission Factor for non-super-emitters in region i
AFi = Activity Factor for region if = Fraction of the Activity Factor attributed to super-emitters
ERi = resulting Emission Rate total for region i
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What do we need to be measuring if the goal is to estimate total emissions?
EFi, super-emitter * (f) AFi,
+ EFi, non-super-emitter * (1-f) AFi, = ERi
EFi, super-emitter = Emission Factor for super-emitters in region iEFi, non-super-emitter = Emission Factor for non-super-emitters in region i
AFi = Activity Factor for region if = Fraction of the Activity Factor attributed to super-emitters
ERi = resulting Emission Rate total for region i
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What do we need to measure if the goal is to reduce emissions to a target level?
EFi, super-emitter * (f) AFi,
+ EFi, non-super-emitter * (1-f) AFi, = ERi
EFi, super-emitter = Emission Factor for super-emitters in region iEFi, non-super-emitter = Emission Factor for non-super-emitters in region i
AFi = Activity Factor for region if = Fraction of the Activity Factor attributed to super-emitters
ERi = resulting Emission Rate total for region i
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Recommendations
• Quantifying super‐emitters• Develop consistency in reporting emissions
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Challenges in reporting emissions• Different portions of the supply chain
– Some studies examine all parts of the supply chain in a region, some focus on specific sources
• Different spatial scales– Some national estimates, some regional estimates, but significant regional differences have been observed
• Different temporal scales– Some instantaneous measurements, some annual averages
• Inconsistent reporting metrics– Tendency to focus on fraction of natural gas used or produced that is emitted, but numerator and denominator in this fraction should be defined precisely and consistently
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Recommendations
• Addressing super‐emitters– Need technologies to rapidly find and fix
• Develop consistency in reporting emissions• More top‐down and bottom‐up studies are needed
• Reconciliations between top‐down and bottom‐up studies need to recognize spatial variability, temporal variability and role of super‐emitters
• More information needed on air toxics• More global information needed