85
The scale of shale resource development is so large that assessing air quality
impacts can be challenging. Unlike PM, VOCs and NOx are gases and can therefore
be dispersed widely across a shale play. The Marcellus play, for example, extends
from the Kentucky-West Virginia border region up to the northeastern corner of
Pennsylvania, a distance of some 450 miles (725 km). Production in the Bakken
Shale covers an area of almost 60,000 square miles (155,400 km
2
) in parts of
Montana, North Dakota, Saskatchewan and Manitoba. Categorizing production
activity and emission sources across such vast areas is difficult.
Fortunately for researchers, a small number of sites tend to contribute a major
proportion of the emissions. These are known as “super-emitters,” and once they are
accounted for, the remaining emissions at multiple scales tend to be within the same
order of magnitude, and can be averaged out for regional estimates (Allen 2016).
Given the size of the shale plays, the number of operators, variability in site design,
construction and maintenance standards, differences in operational approach, and
variations in the oil and gas composition within and among plays, it is almost inevitable that there will be super-emitters among the crowd (Allen et al. 2017).
Linkages between energy production and energy use can also affect regional air
quality, for example, gas production in Colorado’s Wattenberg field coupled with
wintertime gas use in nearby Denver (Ladd 2001). These impacts vary among
regions (Allen 2016).
One way to obtain a better estimate of regional VOC and NOx emissions is to use
computer simulations to run numerical calculations. Two different approaches can
be taken; the first is a process-oriented approach called “bottom-up,” which calculates representative emission rates from different sources multiplied by the number
of sources in a study area (Allen 2014). These rates are then used to tally up the
estimated total emissions from an operation or a set of operations (Townsend-Small
et al. 2015).
The second approach is known as “top-down” and uses observation-oriented
computer models of measured atmospheric concentration data to assign emission
rates to individual sources within the model (Pétron et al. 2014; Nathan et al. 2015).
The presence of super-emitters in the study area can contribute a significant degree
of uncertainty to the estimates from either of these methods. The top-down estimates of fugitive emissions are typically higher than bottom-up estimates at the
basin scale, with larger discrepancies in larger study areas (Vaughn et al. 2018). The
variability in emissions over time when super-emitters are involved may explain
much of the difference (Allen et al. 2017).
5.3 Background Emissions
Some shale gas and tight oil resources are located in remote, rural areas where little
to no air pollution existed prior to development. The Bakken Shale in the sparselypopulated, northwestern corner of North Dakota is one such example. In this case,
assessing the contribution of shale development to the degradation of air quality in
5.3 Background Emissions
The scale of shale resource development is so large that assessing air quality
impacts can be challenging. Unlike PM, VOCs and NOx are gases and can therefore
be dispersed widely across a shale play. The Marcellus play, for example, extends
from the Kentucky-West Virginia border region up to the northeastern corner of
Pennsylvania, a distance of some 450 miles (725 km). Production in the Bakken
Shale covers an area of almost 60,000 square miles (155,400 km
2
) in parts of
Montana, North Dakota, Saskatchewan and Manitoba. Categorizing production
activity and emission sources across such vast areas is difficult.
Fortunately for researchers, a small number of sites tend to contribute a major
proportion of the emissions. These are known as “super-emitters,” and once they are
accounted for, the remaining emissions at multiple scales tend to be within the same
order of magnitude, and can be averaged out for regional estimates (Allen 2016).
Given the size of the shale plays, the number of operators, variability in site design,
construction and maintenance standards, differences in operational approach, and
variations in the oil and gas composition within and among plays, it is almost inevitable that there will be super-emitters among the crowd (Allen et al. 2017).
Linkages between energy production and energy use can also affect regional air
quality, for example, gas production in Colorado’s Wattenberg field coupled with
wintertime gas use in nearby Denver (Ladd 2001). These impacts vary among
regions (Allen 2016).
One way to obtain a better estimate of regional VOC and NOx emissions is to use
computer simulations to run numerical calculations. Two different approaches can
be taken; the first is a process-oriented approach called “bottom-up,” which calculates representative emission rates from different sources multiplied by the number
of sources in a study area (Allen 2014). These rates are then used to tally up the
estimated total emissions from an operation or a set of operations (Townsend-Small
et al. 2015).
The second approach is known as “top-down” and uses observation-oriented
computer models of measured atmospheric concentration data to assign emission
rates to individual sources within the model (Pétron et al. 2014; Nathan et al. 2015).
The presence of super-emitters in the study area can contribute a significant degree
of uncertainty to the estimates from either of these methods. The top-down estimates of fugitive emissions are typically higher than bottom-up estimates at the
basin scale, with larger discrepancies in larger study areas (Vaughn et al. 2018). The
variability in emissions over time when super-emitters are involved may explain
much of the difference (Allen et al. 2017).
5.3 Background Emissions
Some shale gas and tight oil resources are located in remote, rural areas where little
to no air pollution existed prior to development. The Bakken Shale in the sparselypopulated, northwestern corner of North Dakota is one such example. In this case,
assessing the contribution of shale development to the degradation of air quality in
5.3 Background Emissions