THE EFFECT OF AVIATION INDUCED CONTRAIL CIRRUS ON GLOBAL RADIATION
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THE EFFECT OF AVIATION
INDUCED CONTRAIL CIRRUS ON
GLOBAL RADIATION
By Jelmer Dexter Kooij 12064610
Primary assessor: Dr. In. J. H. van Boxel Secondary assessor Dr. K. F. Rijsdijk
Primary supervisor: Dr. In. J. H. van Boxel Secondary supervisor: D. C. Danesh
21-05-2021 Amsterdam
Image: https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/clouds/other-clouds/contrailsAbstract
The increase of radiative forcing is a main driver of global warming. Aviation is known to
affect the radiative forcing on Earth significantly, thus being responsible for a share of global
warming. In order to gain a broader understanding of this system, this research aims to assess
how aviation affects the amount of global radiation. Based on a review of existing literature
concerning the effect of cirrus clouds on global radiation and the contribution of aviation on
cirrus clouds, a quantitative study was conducted comparing observed global radiation data
for hours without cloud cover, to modelled global radiation data under clear skies. This data
was grouped by year, with the 2010-2019 data later to be pooled. By dividing the observed
global radiation data by the modelled data, the global radiation proportions were calculated.
The median global radiation proportions of 2010-2019 and 2020 were then compared using a
one sided one sample T-test. The results of the one sided one sample T-test comparing the
medians of the 2010-2019 period and 2020 show that the global radiation proportion of 2020
does not significantly differ from the 2010-2019 (T-statistic = -0.366). However, literature
suggests that air traffic leads to an increase in cirrus clouds. These (contrail) cirrus clouds
reflect a share of the radiation, which thus decreases the amount of global radiation on Earth.
Therefore it is concluded that less air traffic does increase the amount of global radiation, but
that this effect is practically insignificant when compared to other factors.
1Table of content
Title page .......................................................................................... Fout! Bladwijzer niet gedefinieerd.
Abstract ................................................................................................................................................... 0
Table of content ...................................................................................................................................... 2
Introduction............................................................................................................................................. 3
Methods and Data ................................................................................................................................... 4
Results ..................................................................................................................................................... 6
Conclusion ............................................................................................................................................. 11
Acknowledgements ............................................................................................................................... 12
Bibliography........................................................................................................................................... 13
Appendix................................................................................................................................................ 15
2Introduction
The climate on Earth is changing constantly in a very slow pace. This natural climate
change is caused by shifting concentrations of greenhouse gases in the atmosphere. These
greenhouse gases increase the radiative forcing which affects the radiation budget. This is the
balance of short-wave radiation that Earth absorbs and reflects, as well as the amount of long-
wave radiation that is emitted (Forster et al, 2007). On average, of the 340 W/m2, 100 W/m2 is
reflected back into space by clouds (Hartmann et al, 2013). Due to a shift in the radiative budget
of the Earth’s atmosphere, the climate is slowly changing.
On Earth the amount of greenhouse gases in the atmosphere has increased significantly
during the Anthropocene, largely due to the use of fossil fuels (Solomon et al., 2009). This
causes a rapid change in temperature which affects many natural weather processes and could
potentially disrupt entire ecosystems (Hoegh-Guldberg, 2009). In order to slow down climate
change and prevent Earth’s global average temperature from rinsing more than 1.5℃ it is
important to reduce the amount of greenhouse gases emitted drastically (Eickhout et al., 2004).
In the past some studies have been conducted in order to try to explain and predict the
effect of aviation induced contrail cirrus on the Earth’s radiation budget (Bock and Burkhardt,
2019; Meerkötter et al, 1999). However, due to the Covid-19 pandemic a rare opportunity has
presented itself to study the direct effect of a large reduction in air traffic on the global
radiation
Research has shown that aviation is a relatively large contributor to the amount of
radiative forcing in the atmosphere. Aviation contributes to approximately 1.6% of the total
radiative forcing caused by carbon dioxide (CO2). However, the radiative forcing caused by
contrail cirrus, which results from the emission of water following the combustion of jet fuel at
10-12 kilometre has a far greater effect. In total, aviation contributes to approximately 5% of
the total amount of the anthropogenic radiative forcing as of 2005 (Lee et al, 2009). However,
due to the fact that air traffic is expected to increase over the next few decades, this contribution
is expected to increase as well (ICAO, 2021).
At the high altitude that (contrail) cirrus cloud formations occur, the temperature is
well below freezing and frequently as low as -50℃. Due to the cold air, cloud formations at
this altitude do not exist out of water droplets, but rather ice crystals (Matus and L’Ecuyer,
2017). During overcast conditions when only cirrus clouds are present, approximately 83% of
the radiation is still transmitted, depending on the airmass (Haurwitz, 1946). However,
approximately 25% of this effect is caused by the atmosphere which scatters and absorbs a
share of the radiation (Van Boxel, 2002; Kasten and Czeplak, 1980).
Due to the low temperature at the cruising altitude of aeroplanes (10-12km), the hot,
humid exhaust quickly supersaturates. Following this, water in the exhaust condensates and
subsequently freezes into ice crystals forming contrail cirrus clouds (Schumann, 2005). These
contrails affect the amount of radiation that reaches Earth’s surface in the same manner that
regular cirrus clouds do (Minnis et al, 2013). Thereby, small soot particles in the exhaust may
trigger nucleation of ice crystals in humid air (Schröder et al, 2000). Cirrus cloud cover that
3can be attributed to aviation has increased by 1% to 2% between 1984 and 1999 and due to an
annual increase in jet fuel consumption is expected to keep increasing (Stordal et al, 2005).
In the days following the 9/11 attacks in the United States of America, average
temperatures in the USA rose by 1.1℃, this increase in temperature was to be attributed to the
decrease in contrail cirrus following all commercial aircraft to be grounded for multiple days
(Travis et al, 2002). However other studies, while acknowledging the fact that contrails do
effect the weather system, suggest that this effect might be overestimated (Kalkstein and
Balling, 2004). This shows that the effect that air traffic has on this system is yet poorly
understood. During the COVID-19 pandemic, global air traffic decreased as well in order to
stop the spread of the virus. This makes for an unique opportunity in order to study the effects
of aviation induced contrail cirrus on global radiation. This knowledge attributes to a better
understanding of the effects of contrail cirrus on the radiation budget, temperatures and
possibly global warming.
The aim of this research is to gain insight in how aviation induced contrail cirrus
affects the amount of global radiation on Earth. Therefore, the research question of this
project is; “How does aviation induced contrail cirrus affect global radiation?”. In order to
answer this question two sub-questions will be answered. The first being “How do cirrus
clouds affect global radiation?”. The second “How does aviation affect the amount of cirrus
clouds?”. These sub-questions are answered by studying existing scientific literature and by
comparing observed global radiation under unclouded skies during 2020, a year which had
little air traffic due to the COVID-19 pandemic, to that in normal years.
Taking into account the fact that cirrus clouds have a negative effect on the
transmittance of short-wave radiation of the atmosphere, as well as the fact that air traffic
increases the amount of cirrus clouds in several ways, it seems obvious that higher air traffic
leads to lower global radiation. Therefore the hypothesis of this research is that aviation
induced contrail cirrus decreases the amount of global radiation and that this effect is
significant.
Methods and Data
This research focusses on gaining a deeper understanding in how aviation induced
contrail cirrus affects global radiation on Earth. Firstly, this research uses existing literature on
the effects of cirrus clouds on the amount of global radiation. This helps to gain insight in how
cirrus clouds in general affects the amount of global radiation. Thereby, existing literature is
used in order to asses to what share aviation is responsible for the total amount of cirrus clouds.
Finally, a quantitative research is conducted in order to establish whether global radiation is
significantly different during periods with lower air traffic compared to periods with average
numbers of air traffic.
Due to the COVID-19 pandemic, the amount of air traffic in 2020 has been much lower
than the years before (Eurocontrol, 2021a). The quantitative research focusses on the extend to
which the global radiation on days with a clear sky in the Netherlands in 2020 has varied from
what would be expected under normal circumstances. For this research the KNMI weather
station at Schiphol airport is selected due to its position near high-traffic waypoints, SPY and
PAM, and thus the contrail cirrus is expected to be as highly concentrated as possible
(Eurocontrol, 2021b).
4The majority of this research, the statistical analysis concerning global radiation data on
days from 2010-2020 relies on hourly global radiation data of the Royal Dutch Institute of
Meteorology (KNMI, 2021) and the global radiation model constructed by Van Boxel (2002).
The model has been adapted to the same location as the weather station. For this, the longitude
and the real solar time in the model are adjusted to the values applicable for this weather station.
The model is written in R-studio and copied to an excel spreadsheet. This spreadsheet is
subsequently transferred back into a R-studio data frame..
The observed hourly data for weather station Schiphol are downloaded from the
database of the KNMI (KNMI, 2021). The KNMI data is converted from J/cm2/s to J/m2/h to
make it line up with the model The amount of measurements over the course of the two datasets
used are 87.648 for the 2010-2019 period and 8.784 during 2020. Therefore, these
measurements are firstly grouped into datasets containing just one year. Of these datasets only
the amount of global radiation and the cloud cover for that hour are selected. In order to make
an observed dataset containing all the data for global radiation on cloudless days, since this
eliminates the effect of lower- and middle-altitude clouds, a variable is made that is 1 in case
there is no cloud coverage and 0 in case there is any. By multiplying this layer with all the
observed global radiation data every observation made under a clouded sky will have a value
of 0. Thereafter, the observed data is divided by the modelled global radiation of that hour.
Finally, all data that has a value of 0 or is not available is removed, resulting in the proportion
of observed global radiation compared to the modelled global radiation on hours without any
cloud coverage or Relative Global Radiation (RGR). This results in eleven datasets, one for
each year with the RGR centred approximately around 1, since assuming the model is accurate,
the observed and modelled global radiation should be near identical.
Data containing measurements from the period 2010-2019 are grouped together to form
the control group. After this dataset has been constructed, a statistical analysis is conducted
comparing multiple properties of the data sets. the global radiation proportions of 2020 to the
data of the grouped 2010-2019 data. This one sided one sample T-test inspects whether the
medians of the two groups (RGR in 2010-2019 and RGR in 2020) differ significantly or not.
Comparing the medians of the RGR data is chosen instead of mean since the latter is sensitive
to outliers. For this one sided one sample T-test the mean of the median RGR data and the
standard deviation for 2010-2019 are calculated. Then the T-statistic is calculated by
subtracting the median of 2020 from the mean median of 2010-2019, divided by the standard
deviation, divided by the square root of the sample size (in this case 10).
This methodology was chosen since it is relatively simple and can be applied for any
measurement location that at least registers global radiation and cloud cover, as well as at what
time these measurements were taken. For this research, the at Schiphol located weather station
was the most logical since it has much air traffic flying over. Therefore it is expected to see the
most significant variation in contrail cirrus depending on air traffic. Previous research has
shown that especially near these kind of flight corridors, the amount of aviation induced contrail
cirrus can be significantly higher compared to areas with less air traffic (Yang et al, 2010).
Thereby, the model (Van Boxel, 2002) is constructed for an altitude at sea level, since Schiphol
is situated nearly at sea level, the atmosphere’s turbidity does not vary as much as it would for
locations located high above sea level. Thereby, by choosing hourly data over daily data, which
is also provided by the KNMI, the amount of observations suitable for the analysis is increased
resulting in a more reliable outcome.
5Results
The literature study conducted in this research found that water vapour in the hot air that
is emitted during the combustion of jet fuel may lead to supersaturation of the air. Due to the
supersaturation the water vapour condenses and, due to the low temperature at cruising altitude
(10-12km), subsequently freezes forming ice crystals (Schumann, 2005). These ice crystals
then form contrail cirrus.
The properties of cirrus clouds are different compared to other cloud types which occur
at lower altitudes (Matus and L’Ecuyer, 2017). During cirrus overcast conditions approximately
83% of the short-wave radiation eventually reaches the Earth’s surface, without being absorbed,
reflected or scattered. Of the 17% that is either absorbed, reflected or scattered, about 75% can
be attributed to cirrus clouds, the latter 25% to the atmosphere (Van Boxel 2002). In total,
approximately 14% of the radiation is absorbed or scattered by cirrus clouds and does not reach
the Earth’s surface (Kasten and Czeplak, 1980).
In the northern hemisphere, contrail cirrus clouds cover between 0.40% to 0.07%, with
a mean coverage of 0.13%. However, in higher traffic areas this can be higher than 1.00%
(Duda et al, 2013). Due to the increasing trend of the amount of air traffic, cirrus cloud cover
is increasing by 1% to 2% per decade (Stordal et al, 2005). However, this increase seems to be
more evident in higher latitude areas (Yang et al, 2010). This increase in aviation induced
contrail cirrus decreases the amount of radiation that reaches the Earth’s surface (Minnis et al,
2013). While the amount of global radiation decreases due to radiation being reflected into
space, on the other hand these clouds transmit and absorb the long wave radiation coming from
Earth’s surface. This greenhouse effect of cirrus cloud coverage add up to approximately +1.3
W/m2 of radiative forcing (Chen et al, 2000).
The statistical study in the research compares the hourly data of the amount of global
radiation on hours without any cloud cover. It uses observation data from 2010 until 2020, these
observations are conducted at the weather station at Schiphol airport near Amsterdam.
The relative global radiation (RGR) was defined as the quotient of the observed global
radiation and the modelled global radiation, as can be seen in the methods section. Figure 1
shows the RGR of each year ranging from 2010 to 2020. The boxplots show that the median
RGR value for each year is well nigh a value of 1. A small variation can be noted per year for
the median RGR, as well as the location of the median RGR compared to the quantiles. The
plot also shows that there are quite some outliers for every year, both above and below the
whiskers. In figure 2 just the median values are plotted, here a more clear difference can be
noted between the years. This plot clearly shows that the RGR value was higher than the median
RGR in 2014 and 2020, compared to the other years. Yet, neither of these two median values
are higher than 1.
Figure 3 shows the mean RGR value per year. In this plot it can be seen that not only
2014 and 2020 have a relatively high mean RGR value compared to the average, but also both
2010 and 2012 have a high mean RGR. Thereby, a trend line is plotted which starts at the 11
year mean and increases by 2% per decade.
Figure 4 shows a boxplot of the global radiation proportions compared to the model of
the data of the period 2010-2019 and the year 2020. What stands out in this boxplot is that the
whiskers, both quantiles and the median of the proportion is higher for 2020 than for the period
62010-2019. Furthermore, the year 2002 has only very little outliers on the lower side compared
to the period of 2010-2019.
A one sided one sample T-test was used in order to determine whether the pooled RGR
values of 2010-2019 were smaller than the RGR value for the year 2020. By conducting this
test it is possible to tell whether the 2020 RGR value is significantly higher than the value of
the ten years before the COVID-19 pandemic. With 9 degrees of freedom and a significance
level of α=0.05, the minimal T-statistic in order to reject the null hypothesis that the RGR value
for 2020 is the same as in the ten year period before is 1.833 or -1.833.
Figure 1 showing boxplots for the distributions of the proportion of the observed global radiation compared to the
modelled data at Schiphol for each year.
7Figure 2 showing the median proportion of the observed global radiation compared to the modelled data at Schiphol for each
year.
Figure 3 showing the mean proportion of the observed global radiation compared to the modelled data at Schiphol for each
year (black), as well as a trend of 2% increase per decade starting at the mean value of the period 2010-2020 (red).
8Figure 4 showing boxplots for the distributions of the proportion of the observed global radiation compared to the modelled
data at Schiphol for the pooled data of the period 2010-2019 as well as 2020 on its own.
Discussion
Both the literature as the statistical analysis which are conducted in this study do indicate
that a lower amount of air traffic immediately decreases the amount of contrail cirrus. This in
turn increases the amount of global radiation observed. The result indicates that a higher amount
of air traffic decreases global radiation.
The results of this study show that cirrus cloud formations in general, have high
reflection and absorption properties. Approximately 62% of the short-wave radiation does not
pass through cirrus cloud formations under overcast circumstances. Thereby, 25% of the total
short-wave radiation is either absorbed or scattered by the atmosphere. This results in a 17%
decrease in global radiation compared to a situation in which all the short-wave radiation would
reach Earth’s surface. In all, this contributes to a slight positive net radiative forcing of 1.3
W/m2 (Chen et al, 2000). This would mean the Earth’s atmosphere and surface could slightly
warm up (Campbell et al, 2016).
Due to the possible supersaturation of emitted air following the combustion of jet fuel
at cruising altitude, the water vapour condenses, freezes and forms cirrus cloud formations. On
average, contrail cirrus clouds cover 0.40% to 0.07%, with a mean of 0.13% of Earth’s
atmosphere being covered, with the cover at higher latitudes being higher (Duda et al, 2013)
(Yang et al, 2010). However, in areas with high air traffic, such as near Schiphol airport where
the weather station that is used in the statistical analysis is based, this can be over 1.00%. This
would mean that in areas with a high amount of air traffic, there would be more cirrus cloud
coverage due to the contribution of aviation induced contrail cirrus. This increase in cirrus cloud
coverage, due to its reflecting and absorbing properties, global radiation would be lower
compared to a situation with little to no air traffic.
9The plots have shown that the median RGR for 2020, are higher compared to the ten
year period between 2010 and 2019, for the exception of the median RGR of 2014. When
comparing the mean RGR, we see that besides 2020, 2013 and 2014 are also relatively high
compared to the other observed years. However, this might be due to the high number of outliers
that these years have. Firstly, the 2013 and 2014 data result in a boxplot which has a relatively
large difference between the RGR and the quantiles. They also show whiskers which are
relatively further apart than those of the other years. Thereby they also show some outliers
which are higher compared to these of the other years. All these factors might have affected the
mean to become a little higher. When looking at the median RGR value, it can be observed that
2020 again is relatively large compared to many of the other years in this period. However, the
RGR value of 2014 again is relatively high as well. The proportion value of 2013 is quite low
compared to its mean value, due to the outliers. This gives reason to believe that the mean was
indeed higher than expected due to its high outliers. The same goes for many of the other years,
albeit in smaller proportions, such as the RGR of 2010. What stands out as well is that none of
the median observed global radiation proportions exceed a value of 1. This result is as expected
since it would not make sense that many of the global radiation measurements would be higher
than the potential global radiation.
The results also show that every data set has a relatively high amount of outliers. These
outliers mostly occur where the RGR values are high. However, also a smaller amount of
outliers on the low side can be observed. The high RGR outliers nearly always occur at either
dawn or sunset. Due to the amount of global radiation rising and falling very quickly at these
times of the day, if the model is only slightly off, the relative difference between the model and
the observations by the weather station can be quite large. This is however largely filtered out
by removing all data where either the modelled data or the observed global radiation is lower
than 50. The same goes for the data with a low RGR value. However, there are several more
reasons which may also explain these low values. Firstly, the cloud cover data can be off. When
the cloud cover is larger, this data will have a lower amount of global radiation than under
cloudless conditions. This would result in lower RGR values. Thereby, it is also possible that
the measurement instruments have been temporarily blocked casting a shadow on the
instrument. This does also decrease the amount of global radiation that is registered, resulting
in a lower RGR value.
Due to the relatively large amount of outliers which do occur mostly on the higher RGR
values, the distribution of the RGR values is slightly skewed. Thereby, the means are also
affected by the outliers. As a result, instead of the means, the median for each year is selected
to test the data for 2010-2019 to the 2020 data.
However, in order to give a quantitative answer to determine whether the difference is
significant, a one sided one sample T-test was used in order to determine whether the pooled
RGR values of 2010-2019 were smaller than the RGR value for the year 2020. By conducting
this test it is possible to tell whether the 2020 RGR value is significantly higher than the value
of the ten years before the COVID-19 pandemic. With 9 degrees of freedom and a significance
level of α=0.05, the boundary T-statistics in order to reject the null hypothesis that the RGR
value for 2020 is the same as in the ten year period before is 1.833 or -1.833. The result of the
one sample T-test calculates a T-statistic of -0.366. This value lies within the minimal T-
statistics. This leads us to not reject the null-hypothesis. This means that the RGR value for
2020 is not significantly higher than that of the period 2010-2019 and based on the data used in
10this research, it is not possible to conclude that the reduction in air traffic during 2020 has lead
to a higher amount of global radiation.
By failing to reject the null-hypothesis of the T-test, the initial research hypothesis is
rejected. Since the results found in this statistical analysis do not correspond to the results found
in earlier studies, instead it can be concluded that even though a reduction in air traffic leads to
an increase in global radiation, the effects are insignificant when they are compared to other
factors such as for instance the turbidity of the atmosphere.
What the results add to previous knowledge is that the impact that aviation induced
contrail cirrus on amount of global radiation is insignificant. This is at least, compared to for
instance air pollution and other factors that affect the turbidity of the atmosphere. What the
results of this study do not show however is the expected decrease in global radiation due to the
trend of a 1% to 2% increase in contrail cirrus per decade. This is partly due to the fact that the
variation in the median yearly RGR is much larger than this 1% to 2%. However, this trend
might would be more easily observed when studying observations for a larger time period than
just 11 years.
It should be noted that in the results however, even though 2020 has a higher mean
proportion than the pooled average proportion median of the 2010-2019 period, some others
years stand out as well. Most notably the data for 2014. However, since it is beyond the scope
of this study to address why this unexpected high median value has occurred, the reason for this
phenomenon cannot be answered in this research. This could however be an interesting subject
for future research. This future research is required to establish whether there are any
irregularities which affect global radiation during 2014 compared to other years, in order to
investigate whether the unexpected high median proportion is coincidental or caused by another
factor.
In figure 2 it can be concluded that there have been many instances in which the
observed global radiation was actually higher than the modelled potential global radiation. This
does not make sense since the model is constructed for a situation with a clear sky with neither
cirrus- nor lower- and middle altitude cloud cover. This would mean that either the model is
slightly off and underestimates the amount of global radiation, or the measurements of the
KNMI slightly overestimate the amount of global radiation observed. Therefore in order to
determine which of the two reasons can be held accountable for these slight errors, research
assessing the measurement equipment’s accuracy by comparing them to other equipment could
be conducted. If this proves that the equipment is not slightly off, the global radiation model
could be refined adding additional factors which might play a role.
Other factors however, can also contribute to a variation in global radiation. For
examples changes is the turbidity of the atmosphere as a result of volcanic eruptions or air
pollution. These factors have not been taken into account in this research and thus may have
caused a slight alternation of the global radiation proportions compared to the modelled data.
Conclusion
This research aimed to assess how aviation affects the amount of global radiation. The
literature review conducted in this study indicated that cirrus cloud formations can, under the
right circumstances and taking into account the atmosphere’s turbidity, decrease the amount of
global radiation under overcast conditions by over 17%, resulting in a share of 83% of the short-
11wave radiation that reaches Earth’s surface (Haurwitz, 1946) . Aviation contributes to the
amount of cirrus clouds by oversaturating the air with water vapour as a product of the
combustion of jet fuel as well as soot particles triggering nucleation. Aviation induced contrail
cirrus accounts for approximately 1.00% cover in high-traffic areas, and is more prevalent in
areas with a high latitude. The quantitative research conducted has shown that the proportion
of global radiation compared to the modelled global radiation was not significantly higher in
2020, than the proportion of the period 2010-2019. These results do not match with existing
literature on the topic.
Based on the qualitative and quantitative analysis that have been conducted in this study, it can
be concluded that a higher amount of air traffic, is expected to result in a reduction in global
radiation. However, the effects of contrail cirrus on the amount of global radiation are slim and
thus do not impact the global radiation significantly compared to other factors. The
methodology for the qualitative research has been quite effective since it ended up
approximating the proportion of 1 between the observed KNMI global radiation data and the
modelled data closely. However, new questions that have emerged while conducting this
research. As for example why the median global radiation proportions for the years 2010 and
2014 are as high as they are.
This research shows how aviation induced contrail cirrus effects the amount of global radiation,
albeit in an amount that is too little to differentiate its effect while other factors also effect the
amount of global radiation. Therefore, it may attribute to a more broad understanding about the
way in which aviation induced contrail cirrus affects the entire Earth’s radiation budget. This
can help to assess the role of aviation has as a cause of global warming and what the effects
may be.
Acknowledgements
I would like to thank miss Donya C. Danesh especially for helping me out to get
started on this research. Initially she has helped me with setting up this research a great deal. I
would like to give a special thanks to Dr. Ir. John H. van Boxel who has helped me a great
deal for the entire duration of the research. Especially during the last few week to help me out
with the results. I would also like to thank him for all the time he has invested into me and this
research, outside of the planned personal and group meetings. I am convinced without his
help this research would not exist in this form.
All data that is used for this project is uploaded on figshare.com and is freely
accessible.
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