The wealth of air quality information provided by satellite infrared
observations of ammonia (NH
There is a total of more than
Satellite observations can provide regional and global scale coverage over
relatively long time periods (typically over a 5–15 year time period for a
single sensor). They provide unique observations for air quality monitoring
in and around the Canadian oil sands, as has previously been demonstrated by
the NASA Aura Ozone Monitoring Instrument (OMI) nitrogen dioxide (NO
Ammonia is a short-lived gas, often only residing in the atmosphere from
hours to a day (Seinfeld and Pandis, 1998; Aneja et al., 2001). It is an
important base that reacts in the atmosphere with sulphuric acid
(H
Methanol (CH
Formic acid (HCOOH) is a dominant source of atmospheric acidity and is the
dominant contributor (60–80 %) to acid rain over boreal forest regions
(i.e. surrounding the oil sands operations; Stavrakou et al., 2012). Thus,
it is important for pH-dependent processes in the atmosphere. The main
source of atmospheric formic acid is secondary photochemical production
(Millet et al., 2015) from precursors including isoprene, monoterpenes,
other terminal alkenes (e.g. Neeb et al., 1997; Lee et al., 2006; Paulot et
al., 2011), and alkynes (Hatakeyama et al., 1986; Bohn et al., 1996). Direct
emissions of formic acid are thought to be smaller and include biomass and
biofuel burning (e.g. Goode et al., 2000), biogenic emissions from plants
and soils (e.g. Kesselmeier et al., 1998; Kuhn et al., 2002; Jardine et
al., 2011; Sanhueza and Andreae, 1991), agriculture (e.g. Ngwabie et al.,
2008), and urban emissions (e.g. Kawamura et al., 1985; Talbot et al.,
1988). Formic acid is a major contributor to acid rain in remote
environments (Keene and Galloway, 1988; Andreae et al., 1988) and reduces
the pH in rainwater by 0.25–0.5 units over boreal forests and Amazonia in
the summertime, accounting for as much as 60–80 % of the rainwater
acidity over these remote regions in the summer (Stavrakou et al., 2012).
The average lifetime of formic acid is
Carbon monoxide (CO) is one of the primary atmospheric pollutants and listed as a Canadian CACs (Environment Canada, 2013). CO is a colourless toxic gas that can have severe effects on human health (e.g. Burnett et al., 1998a, b). The role of CO in tropospheric chemistry and climate is well established (Logan et al., 1981; Shindell et al., 2006). In addition to its photochemical source from the oxidation of methane and other VOCs, sources of CO is incomplete combustion, which occurs in open fires, domestic biofuel use, vehicle use, and industrial activities. Reaction with the hydroxyl radical (OH) is the main removal process for CO. The lifetime of CO is a few weeks in mid-to-high latitudes, long enough to allow intercontinental transport. Satellite observations of global CO have been made by multiple sensors over the past decades (Deeter et al., 2014; McMillan et al., 2011; Luo et al., 2007a; George et al., 2009).
In addition to the information provided by each satellite-retrieved species
on its own, the relatively short-lived species including ammonia, methanol,
and formic acid can be used with other simultaneously retrieved species to
provide ratios (tracers) that can be used for identifying and constraining
sources (i.e. biomass burning or biogenic emissions; e.g. Coheur et al.,
2009; Wells et al., 2014; Luo et al., 2015); if the species has a longer
lifetime, as does CO, the ratios can also be used for determining loss
rates. As an example of source identification, a high correlation between
HCOOH and CH
Satellite observations of these species are inferred from measured spectral radiances, which generally require a complex retrieval inversion process with assumptions on the profile shape and its variability (e.g. Bowman et al., 2006; Shephard et al., 2011; Cady-Pereira et al., 2012, 2014). The available retrieval information from these species is limited as the infrared spectral signal is often less than 0.3 % (or less < 1 K brightness temperature) of the total background signal (on the order of 300 K brightness temperature). Thus, these satellite retrievals can be challenging and require validation against other available observations. To this end, aircraft observations from the intensive Joint Canada–Alberta Oil Sands Monitoring (JOSM) air component field campaign held over the oil sands region during August and September of 2013 are used. One of the goals of the aircraft campaign was to validate satellite observations with coincident aircraft in situ observations in order to obtain better estimates on the capabilities and errors of the satellite retrievals in this environment.
In general it is inherently difficult to validate the satellite data with in
situ observations due to the nature of the remote sensing sampling,
especially if the species of interest varies significantly in space or time
in the atmosphere (e.g. Shephard et al., 2008a). Also, in situ vertical
profile measurements of these compounds from aircraft require fast response
instrumentation that has not been available until recently. Thus, to date
there have been relatively few coincident “validation” profiles for the
more recently developed NH
Also provided are initial TES comparisons against Environment Canada's
Global Environmental Multi-scale – Modelling Air quality and CHemistry
(GEM-MACH) model (Makar et al., 2015a, b) runs simulated at a high resolution
of 2.5
TES is a Fourier transform spectrometer (FTS) sensor that was launched on
the NASA Aura satellite on 15 July 2004 (Beer et al., 2001). It is a well
calibrated high-spectral-resolution FTS (0.10 cm
In addition to TES's original standard products, NH
Summary of reported estimates of TES retrieval errors.
As presently there are no actual errors based on direct profile comparisons
for NH
Another characteristic that needs to be taken into consideration for
satellite infrared retrievals of NH
The aircraft flight tracks for flights 18 and 20 and the TES
transect of 5
Model-generated back trajectories for JOSM flight 20 on
5 September 2013 over the Canadian oil sands region plotted spatially as a
function of local standard time (LST). The boundaries of the oil sands region
are outlined with black lines, with the surface mining areas indicated within
this region near the centre of the plot. Each aircraft “profile” (either
the up or down profile) is indicated alphabetically in measurement succession
during the afternoon (e.g. “A” is at 13:22 LST (TES overpass time) and
“E” later in the afternoon at 17:00 LST). Plotted for each of these
aircraft profiles are two back trajectories plotted corresponding to the
lowest aircraft altitude and the
This analysis mainly focuses on the TES satellite observations of NH
During the aircraft component of the JOSM field campaign there were
dedicated aircraft observations made from the National Research Council
Institute for Aerospace Research (NRC Aerospace) Convair-580 research
aircraft that included flights designed for satellite validations. The
unusually large number of cloudy days during the first part of the campaign
limited the number of flights suitable for TES validation purposes. The
dedicated aircraft spiral profiles near Fort MacKay, Alberta, that were
coincident with the TES overpass for satellite validation purposes occurred
on 3 September (flight 18) and 5 September (flight 20) in 2013. These days
were selected during the campaign for periods when there were scheduled TES
oil sands special observations, and the atmosphere was relatively
cloud free. Figure 1 shows the flight tracks
coloured as a function of relative aircraft altitude for flights 18 and 20.
Since the TES special oil sands transects were designed so that the oil
sands surface mining region was near the middle of the
NH
CO measurements were made with an off-axis integrated cavity output
spectrometer (CO-23r; Los Gatos Research Inc., Mountain View, CA; Provencal
et al., 2005) at 2 Hz, and averaged to 1 Hz. CO mixing ratios for the
project ranged from 74 to 774 ppbv with a mean of 110
A proton transfer–time of flight–mass spectrometer (PTR-ToF-MS, Ionicon
Analytik) was used to measure VOCs on the aircraft. Details of the PTR-ToF-MS
technique have been described previously (Jordan et al., 2009; Graus et al.,
2010). Briefly, this instrument uses soft ionization of target VOC compounds
with H
Formic acid measurements were conducted with an HR-ToF-CIMS (Aerodyne
Research Inc.) using acetate reagent ion (A-CIMS). A detailed description of
the instrument and principles of operation have been given elsewhere
(Bertram et al., 2011; Lee et al, 2014). To reduce the residence time in the
overall sampling manifold, the total flow was maintained at > 15 L min
The model used by Environment Canada for the JOSM oil sands simulations is
GEM-MACH. GEM-MACH is a comprehensive air quality simulation system which
operates in an online configuration with Environment Canada's
meteorological forecast model (GEM). It was first described in Moran et al. (2010), and a recent intercomparison between GEM-MACH and other air quality
models using annual observations can be found in Im et al. (2015a, b) and
Makar et al. (2015a, b). Note that the direct and indirect aerosol feedback
effects were not included in these simulations. A three-level nested grid
version of GEM-MACH model is used in the simulations over Canadian oil sands
region, where the innermost and highest-resolution grid has a grid size of
643
The comparison approach selected depends on the goals of the study and the
quantities being compared. Since the main goal here is to validate just the
retrieved information provided by satellite measurements it is often
desirable to perform a profile comparison using the satellite observation
operator, especially for species with limited information content. This
approach provides direct comparisons of the satellite-retrieved quantities
by taking into consideration the reduced vertical resolution of the
retrieved values, as well as removing the influence of the a priori
information (e.g. profile shape) used in the inversion of the
satellite observed radiances to concentration values at each level.
Alternatively, if the comparison is performed on the retrieved profiles
(observed atmospheric state
Since the TES retrievals use an optimal estimation approach this direct
comparison is achieved in a straight-forward manner by applying the
satellite observation operator to the comparison profile,
There are typically greater than 200 instantaneous aircraft observations
being averaged onto each coarse satellite profile level used in these
comparisons. Thus, assuming uncorrelated aircraft observations with similar
levels of uncertainty, the weighted mean aircraft values,
Flight 20 on 5 September 2013 was a transformation flight where the plume
from the oil sands surface mining region was tracked and sampled downwind
from the TES overpass time for several hours. In order to match the
instantaneous satellite overpass observations along the
The aircraft profiles used in the comparison are the two coincident spirals
from flight 18 and the five sets of upward and downward profiles consisting of
the high-altitude spirals at the TES overpass time and four smaller lower-altitude partial sets of profiles later in the afternoon from flight 20.
Each of these aircraft profiles were compared against as many valid TES-retrieved profiles as possible that were
Although back trajectories were conducted to provide guidance on the spatial and temporal coincidence criteria for the comparisons, the lack of variability of these short-lived species over this region during these two flights greatly reduces the sensitivity of the selected coincidence criteria. This can be seen in the aircraft observations as a function of time (refer to aircraft flight observations in plot (b) of the individual comparison figures shown below). Also, as an additional test we repeated the summary comparison analysis for each species without applying any coincidence criteria and the statistical results (not shown) do not significantly vary from the results using the selected coincidence criteria based on the back trajectories shown in this analysis. It should be noted that this is not generally the case for short-lived minor species with localized emission sources such as ammonia. This is more indicative of “background” regional amounts, which is consistent with the more homogeneous regional nature of the concentrations typically seen across the TES special transect observations over this region during the 2012–2014 period.
As the total number of profiles in the summary statistics is relatively small, we report a median value for the bias and the standard deviation derived from the robust median absolute deviation for the variability (Leys et al., 2013), which are more robust statistics that are less influenced by outliers.
As the goal of the comparisons in this study is to validate the satellite observations, the TES observation operator in Eq. (2) was applied to all the aircraft profiles to account for both the reduced vertical resolution of the satellite data and the influence of any a priori information (i.e. profile shape). The aircraft profiles were extended to the full vertical range of the satellite by scaling the a priori profile to match the ends of the aircraft profile (using the shape of the a priori profile). To reduce the impact of numerical errors when applying the log-space observation operator at upper levels, where the concentrations are orders of magnitude smaller than in the troposphere with virtually no associated averaging kernel values (i.e. Worden et al., 2013), a linearized observation operator was applied and the levels between 100 hPa and 0.1 hPa were combined into one. It is also valuable to compare the actual error statistics derived from these TES/aircraft comparisons with the estimated profile errors routine calculated and reported for each observation. Note that the observation error estimates from the operational TES retrieval are reported and plotted in this analysis for comparison purposes (as opposed to the total error estimates) as the TES observation operator has already been applied to the comparison profiles, which takes into consideration the smoothing error component (Shephard and Cady-Pereira, 2015). The retrieval observation error estimates vary depending on the atmospheric conditions. Thus, for representative comparison purposes during JOSM the operational retrieval estimated observation errors at selected levels from the examples in the following sections are provided in Table 2 for reference.
TES operational retrieval observation error estimates for JOSM examples. Note: pressure levels in bold are the average TES peak sensitivity levels for the conditions during these JOSM observations. Additional reported levels are provided for comparison purposes with previous studies.
A representative aircraft/satellite comparison for a single
CH
Presented in Fig. 3 is a comparison for a
single methanol TES/aircraft example profile from flight 18 for the downward
part of the spiral that was coincident with the TES overpass. The rows of
the TES averaging kernel in Fig. 3a show
that the peak CH
Summary box-and-whisker plots of the satellite/aircraft
comparisons during JOSM for CH
A summary of the CH
A similar comparison to the one reported above for CH
Representative single CO profile aircraft/satellite comparison and associated plots. Plotted is the downward aircraft spiral of profile “A” compared with pixel 12 along the TES transect. Plotting convention is the same as Fig. 3.
A summary of all the flight 18 and 20 comparisons for CO is provided in
Fig. 6. Under the atmospheric loading
conditions during this intensive observation period TES-retrieved a median
value of 100 ppbv with a TES/aircraft bias difference of
Summary box-and-whisker plots of the satellite and aircraft comparisons during JOSM for CO, with the same plotting convention as Fig. 4.
The formic acid profile comparisons are somewhat limited due to the aircraft
instrument issues at higher altitudes as noted in Sect. 2.2.4. However, there were still many partial
profile comparison opportunities where the aircraft observations extended to
the TES peak sensitivity level (
Representative single HCOOH profile aircraft/satellite comparison and associated plots. Plotted similarly as Fig. 3, but this is profile “D” from the transformation flight 20 compared with pixel 14 from the TES transect.
The summary values generated from all the available profile comparison
values from flights 18 and 20 are presented in
Fig. 8. This figure shows that at the peak
TES sensitivity level of 750 hPa the median retrieved profile value is 1.04 ppbv with a bias of 0.19 ppbv (
Summary box-and-whisker plots of the satellite and aircraft comparisons during JOSM for HCOOH, with the same plotting convention as Fig. 4.
Figure 9 contains an example profile
comparison of TES pixel 7 with partial aircraft profile “B”
(Fig. 9b). Figure 9a shows the peak sensitivity level of the TES NH
Representative single NH
Figure 10 contains the summary results from
all the available comparisons for NH
Summary box-and-whisker plots of the satellite and aircraft
comparisons during JOSM flight 20 for NH
Summary plot of the actual errors (TES/aircraft) from the JOSM
comparisons plotted as a function of pressure for NH
Summary plot of the actual errors (TES/aircraft) from the JOSM
comparisons plotted as a function of volume mixing ratio (VMR) for NH
For convenience all the altitude comparisons previous presented and discussed in detail for each species are provided in Fig. 11. This allows for the intercomparisons of the errors associated with each of the species analysed in this study for this period over the Canadian oil sands region as a function of pressure. It also present the results in a similar to the magnitude summary figure provided in the next section.
In the previous sections we showed the actual errors as a function of
height. In addition it is also useful to report the actual comparison errors
as a function of the species volume mixing ratio in both absolute and
relative terms. Figure 12 shows the results
from the satellite/aircraft comparisons with the differences binned by the
magnitude of the observations, as opposed to by altitude as shown
previously. For consistency, the same data screening was used as before in
that each profile selected has at least 0.5 DOFS and each level selected has
a diagonal averaging kernel value of at least 0.05. Note that bins were only
reported when they had at least 10 data points, and data points were not
included for retrieval pressure levels above
Single CO profile GEM-MACH model/satellite comparison and
associated plots.
The validated TES observations over the oil sands region can be used with
more confidence for a variety of applications. Provide here are examples of
using the satellite observations for initial model evaluation.
Satellite/model comparisons are performed from both ammonia and carbon
monoxide as formic acid and methanol are not specifically modelled in
GEM-MACH and available for satellite comparisons. The satellite/model
comparisons were performed following the same procedure as the
satellite/aircraft in that the TES observation operator was also applied to
the model profile, which accounted for the satellite retrieval a priori and
vertical sensitivity (i.e. vertical resolution). The main difference is that
the match-ups do not have the same space and time constraints of the
satellite/aircraft comparisons since the model provides a 3-D field of
observations at a time step of 2 min for the chemistry. All the
available model simulations for the full JOSM campaign period were searched
for matchups with the TES transects collected on seven different days.
Unlike the aircraft comparisons, each TES pixel was compared against just
the closest simulation. Note that it would be possible to extend these
comparisons to cover the already completed 2-year period of the TES
special oil sands observations provided that the high-resolution oil sand
model simulations are generated. For this initial comparison just the 2.5
Summary box-and-whisker plots of the satellite and model comparisons during JOSM for CO using the same plotting convention as Fig. 4.
Presented in Figs. 13 and 14 are the initial satellite/model CO
comparison results. The single profile comparison example is from 3 September 2013 for TES pixel 12 at 13:31 LST, which corresponds to the
TES/aircraft comparison in Fig. 5 and is one
of the pixels directly over the oil sands mining region. For this profile
both the TES/aircraft (
Single NH
A summary of the CO satellite/model comparisons for all co-located and
coincident profiles that meet the DOFS
Summary box-and-whisker plots of the satellite and model
comparisons during JOSM for NH
TES/aircraft comparison statistics (actual errors) at peak satellite sensitivity level during JOSM.
Ammonia has not been extensively validated in the GEM-MACH model. Presented
in Figs. 15 and 16 are the initial satellite/model
comparison results. Figure 15 is a single
profile comparison example from 5 September 2013, which is the same
day as aircraft flight 20. Pixel 7 is compared with the coincident and
co-located model profile, which corresponds to the same TES pixel that was
compared with the aircraft profile in Fig. 9
(note that the aircraft observations were taken about 1 h after the
satellite overpass). The noticeable difference in this model comparison is
the much lower ammonia levels (
A summary of the NH
Presented in this study are TES actual errors derived from comparisons with aircraft observations taken during the intensive field campaign over the oil sands region in Alberta, Canada. The comparison results are from the aircraft observations designed to be coincident with the Aura TES overpass times for two flights with clear-sky conditions at the beginning of September 2013. Even with the dedicated validation satellite/aircraft observations, the comparison results represent a limited range of sampling conditions that occurred during this intensive study period (i.e. they do not span the full magnitude range that can be observed by TES globally under many atmospheric conditions). In this analysis we are fortunate to have comparison values of the exact quantity being retrieved (i.e. volume mixing ratio values at profile levels) and a retrieval procedure that provides the vertical sensitivity (i.e. averaging kernels) for each profile so that we can directly validate the satellite observations and not the impact of the a priori profile selection. Thus, we do not need to rely on other indirect methods to try to account for the vertical resolution and the influence of the a priori information (i.e. compute the representative volume mixing ratio; Shephard et al., 2011), which is often required when comparing different quantities (i.e. single column or surface observations) when there is limited information content. The TES/aircraft profile comparison average differences for these atmospheric conditions are presented in Table 3.
These actual errors generally compare well with both the estimated retrieval
observation errors from previous studies (Table 1)
and estimated errors reported in the TES operational retrieval product for
these atmospheric conditions (Table 2). However,
there are some notable exceptions that require further investigation with
additional validation observations: (i) the relatively large negative bias
of
In addition to the aircraft comparisons, the satellite retrievals of ammonia
and carbon monoxide were compared against special high-resolution model
simulations carried out over the oil sands region during the JOSM field
campaign. Only ammonia and carbon monoxide model comparisons were performed
as GEM-MACH does not explicitly model formic acid and methanol. These
initial comparisons identified a general underprediction of ammonia
concentrations by the model relative to both aircraft and satellite
observations. This apparent underprediction of ammonia concentrations from
the satellite/model comparisons of
We would like to thank Susan S. Kulawik for helping provide us with the original updated TES version 6 lite files and Craig Stroud for his helpful discussions and support with the back-trajectory analysis. We would like to acknowledge other members of the aircraft team for their contributions to the airborne measurements used to validate the satellite observations, in particular Andrew Budden, Stewart Cober, Andrea Darlington, Andrew Elford, Anthony Liu, Peter Liu, Aaron McCay, Robert McLaren, Bill McMurty, Richard L. Mittermeier, Julie Narayan, Jason O'Brien, Andrew Sheppard, Ka Sung, Danny Wang, Mohammad Wasey, and the National Research Council Flight Research Laboratory team. We would also like thank the other members of the oil sands modelling working group for their insights on the initial GEM-MACH ammonia simulations over the oil sands region, in particular Michael Moran. Work at the University of Minnesota was supported by NSF (grant no. 1148951). Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official agency policy. This study was supported in part by the Joint Canada–Alberta Implementation Plan for Oil Sands Monitoring, the Clean Air Regulatory Agenda (CARA), and NASA ACMAP (grant no. NNX10AG63G). Edited by: M. Weber