87
Different activities produce different emissions. For example, the highest emissions of PM 2.5 , especially DPM, are most likely to occur when the diesel generators
and pump trucks are used during the drilling and fracking process. NOx from internal combustion engines may also be high during this period. Once the well begins
producing, emissions are more likely to consist of VOCs and methane from the
produced water. Methane emissions at a Marcellus Shale research site were found
to be highest during the initial production of flowback water (Pekney et al. 2018).
Understanding air pollution in the context of daily operations taking place on the
well pad is critically important for monitoring the air quality.
Many of the volatile chemicals associated with fracking are known, but others
remain proprietary and trying to figure out what to measure in the air remains a
major challenge. This is further complicated by reactions at high temperature and
pressure between the fracking additives and rocks in the subsurface, which can
return new chemical species in the produced water (Allen 2016). The measurement
of air emissions from individual shale gas and tight oil production sites has been
carried out at many locations using a variety of methods, including surrogates,
tracer gases like acetylene, direct measurements of specific chemical compounds,
and downwind plume monitoring (Nathan et al. 2015; Pekney et al. 2018).
Because of concerns over fugitive emissions, significant efforts have been
focused on methane detection (Johnson et al. 2019). However, emissions of other
compounds have been associated with shale gas and tight oil development, including VOCs, NOx, black carbon, PM, and radon gas (Casey et al. 2015; Goetz et al.
2017; Bari and Kindzierski 2018; Allshouse et al. 2019; Xu et al. 2019). Technology
for the quantitative analysis of a wide variety of organic chemicals in the atmosphere is expensive, exotic, and not easy to adapt to the field. Thus, many air monitoring operations have been working to develop indicators, surrogates, or tracers
that are more easily detectable (Pekney et al. 2018).
Chemical transport modeling is another approach for quantifying the possible
links between chemical compounds in the atmosphere and potential O&G sources
(i.e. wellsite flaring or a leaking compressor station). These mathematical models
typically use measured chemical concentrations in air combined with meteorological data to try to define the movement of pollutants from sources to potential receptors in the surrounding populations (Pekney et al. 2018). Statistical techniques such
as source apportionment modeling can be used in areas with background levels of
pollutants to try to disentangle O&G emissions from other sources (Bari and
Kindzierski 2018). The spatial and temporal variability in emissions complicates
modeling, along with the subtle details of atmospheric transport at different scales.
Another important consideration is that some of the significant sources are off-site,
such as mobile emissions from heavy trucks transporting material to and from the
well pad. More robust data sets needed for useful atmospheric chemical transport
models include long and short-term variability in pollutant concentrations, documentation of a complete exposure pathway from source to receptor, and links that
connect chemical concentrations at the source to concentrations in nearby communities where people might be exposed (Zielinska et al. 2014).
5.3 Background Emissions
Different activities produce different emissions. For example, the highest emissions of PM 2.5 , especially DPM, are most likely to occur when the diesel generators
and pump trucks are used during the drilling and fracking process. NOx from internal combustion engines may also be high during this period. Once the well begins
producing, emissions are more likely to consist of VOCs and methane from the
produced water. Methane emissions at a Marcellus Shale research site were found
to be highest during the initial production of flowback water (Pekney et al. 2018).
Understanding air pollution in the context of daily operations taking place on the
well pad is critically important for monitoring the air quality.
Many of the volatile chemicals associated with fracking are known, but others
remain proprietary and trying to figure out what to measure in the air remains a
major challenge. This is further complicated by reactions at high temperature and
pressure between the fracking additives and rocks in the subsurface, which can
return new chemical species in the produced water (Allen 2016). The measurement
of air emissions from individual shale gas and tight oil production sites has been
carried out at many locations using a variety of methods, including surrogates,
tracer gases like acetylene, direct measurements of specific chemical compounds,
and downwind plume monitoring (Nathan et al. 2015; Pekney et al. 2018).
Because of concerns over fugitive emissions, significant efforts have been
focused on methane detection (Johnson et al. 2019). However, emissions of other
compounds have been associated with shale gas and tight oil development, including VOCs, NOx, black carbon, PM, and radon gas (Casey et al. 2015; Goetz et al.
2017; Bari and Kindzierski 2018; Allshouse et al. 2019; Xu et al. 2019). Technology
for the quantitative analysis of a wide variety of organic chemicals in the atmosphere is expensive, exotic, and not easy to adapt to the field. Thus, many air monitoring operations have been working to develop indicators, surrogates, or tracers
that are more easily detectable (Pekney et al. 2018).
Chemical transport modeling is another approach for quantifying the possible
links between chemical compounds in the atmosphere and potential O&G sources
(i.e. wellsite flaring or a leaking compressor station). These mathematical models
typically use measured chemical concentrations in air combined with meteorological data to try to define the movement of pollutants from sources to potential receptors in the surrounding populations (Pekney et al. 2018). Statistical techniques such
as source apportionment modeling can be used in areas with background levels of
pollutants to try to disentangle O&G emissions from other sources (Bari and
Kindzierski 2018). The spatial and temporal variability in emissions complicates
modeling, along with the subtle details of atmospheric transport at different scales.
Another important consideration is that some of the significant sources are off-site,
such as mobile emissions from heavy trucks transporting material to and from the
well pad. More robust data sets needed for useful atmospheric chemical transport
models include long and short-term variability in pollutant concentrations, documentation of a complete exposure pathway from source to receptor, and links that
connect chemical concentrations at the source to concentrations in nearby communities where people might be exposed (Zielinska et al. 2014).
5.3 Background Emissions