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# Spatiotemporal monitoring of Methane over Iraq during 2003-2015: retrieved from Atmospheric Infrared Sounder (AIRS)

Authors:
• Mustansiriyah University
• Mustansiriyah University

## Abstract and Figures

Observations of methane (CH4) retrieved from Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua platform from 2003-2015 show a strong, plume-like enhancement of CH4 over central and southern-east parts of Iraq during August - September, with the maximum occurring in early September and minimum in March - May over western, southwest, and north-east regions. The percentage change differences results shows the highest differences occurred over the central and southern regions and the smallest differences occurred over the western and southwest regions. To better validate the retrieved data from AIRS three stations at different locations were chosen for trend analysis. The mean and standard deviation in Mosul, Baghdad and Basrah was (3.610 ± 0.042, 3.818 ± 0.048, 3.824 ± 0.055) x10 19 Mole.Cm -2 respectively for monthly long term trend analysis. Annual trend analysis shows positive trends, and ranged between (0.0083 and 0.0097) Mole.Cm -2 .y -1 for Mosul and Basrah, respectively. Monthly trend analysis have positive trends (0.0092) Mole.Cm -2 .y -1 for Mosul and (0.0107) Mole.Cm -2 .y -1 for Baghdad and Basrah. The annual linear growth rate were (2%) for Mosul, and (3%) for Baghdad and Basrah, and monthly linear growth rates were (5%) for Mosul and Baghdad, and (6%) for Basrah. Further daily long term trend shows significant linear increase of (3.7 %) caused a trend of (0.0107 × 10 19 ) Mole.Cm -2 .y -1 in Baghdad. The standard deviation of variation in daily average CH4 as a percentage deviation from the mean for the departure from the mean was (1.62%), (0.06×10 19 Mole.Cm -2 ). And the day to day variation with a clear seasonal change shows standard deviation of enter sequential changes was (0.053 × 10 19 ) Mole.Cm -2 . These results indicate that Satellite observations efficiently show the temporal variations of the CH4 values over different regions.
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VOL. 13, NO. 22, NOVEMBER 2018 ISSN 1819-6608
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SPATIOTEMPORAL MONITORING OF METHANE OVER IRAQ DURING
SOUNDER (AIRS)
Faten G. Abed1, Ali M. Al-Salihi2 and Jasim M. Rajab3
1Atmosphere and Space Center, Directorate of Space Technology and Communication, Ministry of Sciences and Technology,
2Department of Atmospheric Sciences, College of Science, Mustansiriyah University, Baghdad, Iraq
3Department of Physics, College of Education, University of Al-Hamdaniya, Nineveh, Iraq
E-Mail: alialsalihi.atmsc@uomustansiriyah.edu.iq
ABSTRACT
Observations of methane (CH4) retrieved from Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua platform
from 2003-2015 show a strong, plume-like enhancement of CH4 over central and southern-east parts of Iraq during August
- September, with the maximum occurring in early September and minimum in March - May over western, southwest, and
north-east regions. The percentage change differences results shows the highest differences occurred over the central and
southern regions and the smallest differences occurred over the western and southwest regions. To better validate the
retrieved data from AIRS three stations at different locations were chosen for trend analysis. The mean and standard
deviation in Mosul, Baghdad and Basrah was (3.610 ± 0.042, 3.818 ± 0.048, 3.824 ± 0.055) x10 19 Mole.Cm-2 respectively
for monthly long term trend analysis. Annual trend analysis shows positive trends, and ranged between (0.0083 and
0.0097) Mole.Cm-2.y-1 for Mosul and Basrah, respectively. Monthly trend analysis have positive trends (0.0092) Mole.Cm-
2.y-1 for Mosul and (0.0107) Mole.Cm-2.y-1 for Baghdad and Basrah. The annual linear growth rate were (2%) for Mosul,
and (3%) for Baghdad and Basrah, and monthly linear growth rates were (5%) for Mosul and Baghdad, and (6%) for
Basrah. Further daily long term trend shows significant linear increase of (3.7 %) caused a trend of (0.0107 × 1019)
Mole.Cm-2.y-1 in Baghdad. The standard deviation of variation in daily average CH4 as a percentage deviation from the
mean for the departure from the mean was (1.62%), (0.06×1019 Mole.Cm-2). And the day to day variation with a clear
seasonal change shows standard deviation of enter sequential changes was (0.053 × 10 19) Mole.Cm-2. These results indicate
that Satellite observations efficiently show the temporal variations of the CH4 values over different regions.
Keywords: methane, AIRS, remote sensing.
INTRODUCTION
The Atmospheric methane (CH4) is a second
most potent anthropogenic greenhouse gas (GHGs) only to
CO2, and plays an important role in atmospheric
chemistry. Since 1750, the major source of changing
climate and earths energy balance is increased the
anthropogenic emission of GHGs considerably due to
human activities. The CO2 contributed by 60% and CH4
with 15 to 25% (Lagzi et al., 2014, Bartlett and Harriss,
1993). The fossil fuels, rice paddies, landfill wastes and
livestock have been reported as 60% of CH4 sources with
an average lifetime of 12 years (Rajab et al., 2012). In
absorbing long- wave radiation, the CH4 25 times more
effective on per unite mass basis than CO2, and worm's
planet 86 times as much as CO2(Bernstein et al., 2008,
Pachauri et al., 2014). Its concentrations increased more
than doubled since preindustrial revolution with a current
globally averaged mixing ratio of 1.750 ppbv, and began
to ascend again in 2007 after a decade of near-zero growth
(Wuebbles and Hayhoe, 2002, Wang et al., 2016) .
It might be the stability of CH4 measurements
during 1999-2006 include: an decrease in wetland
emissions and coincident increase in anthropogenic
emissions (Bousquet et al., 2006); a combination of
stable-to-increasing microbial emissions and decreasing-to
stable fossil fuel emissions (Kirschke et al., 2013); and
decreased northern hemisphere microbial sources (Kai et
al., 2011). Might be few reasons for the renewed increase
of CH4 concentrations after 2006 been suggested such as;
the increase of anthropogenic contribution in the northern
hemisphere at tropics and mid-latitudes during the period
2007-2010 (Bergamaschi et al., 2013), from agriculture
(Schaefer et al., 2016), the growth emissions from oil- and
gas use and production during 2007-2014 (Hausmann et
al., 2016), and the expansion of wetland emissions during
2007 and 2008 in either the tropics, due to greater than
average precipitation, and/or in the Arctic, because of high
temperatures (Dlugokencky et al., 2009).
The CH4 formed and emitted to the atmosphere
by biological processes occurring in anaerobic
environments. Many sources released CH4 into the
atmosphere; biogenic (natural and anthropogenic) and
non-biogenic (geological).the natural sources include
wetlands, termites, livestock, ocean, hydrates, wild
animals and wild fires, but the anthropogenic sources are
rice agriculture, landfills, biomass burning, energy and
industry like fossil fuel (Wuebbles and Hayhoe, 2002)
.The single largest sources of CH4 into the atmosphere is
wetlands due to their saturated soils, which account about
20-40% of the global CH4 sources (Rajab et al., 2012).
The growth rates of atmospheric CH4 is determine by the
balance between surface emissions and chemical
distraction by hydroxyl radicals, the most atmospheric
oxidant (Bousquet et al., 2006).
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Prediction of CH4 evolution in the atmosphere
needs knowledge for the sinks and sources. In the earth's
atmosphere, the CH4 absorbs and emits infrared and
causes 4-9% of the greenhouse effect (Blais and Lorrain,
2005). The tropical wetlands dominated by marshes and
swamps emit large amount of CH4 into the atmosphere
compare to the northern peat lands. In addition, the CH4
emissions are higher in open peat lands than the forested
peat lands, this related to the increase in water table depth
and temperature (Melling et al., 2005) . The exchange of
CH4 between atmosphere and the ecosystems depends on
the climate by influencing CH4 production, oxidation and
transport in soil (Spahni et al., 2011).
Tropospheric hydroxyl radicals (OH) are the
major sink for methane besides two other minor sinks
which are dry soil oxidation and transport to the
stratosphere, hydroxyl radicals (OH) take place in the
troposphere, the lowermost part of atmosphere , ranged
between (7-16) Km, which is depending on the latitude
and season , and containing 80% of the atmosphere mass
(Lagzi et al., 2014). Always people have contended with
excessive heat, dust storms, shortage of rainfall and harsh
geography across the Middle East area. During last
century industrial development, climate change, political
upheaval and war had left a legacy of environmental
influences and health problems (Jasim et al., 2010).
The elevation of CH4 concentration is more
challenging for Asia developing countries and indirectly
affecting the developed world, which have less emission
controls and throw significant amount of CH4 to
atmosphere (Atique et al., 2014). In addition, the
percentage Change in CH4 Emissions Between 1990 and
2020 at Middle East was 179% (Kreft et al., 2015). Iraq is
one of the middle east country, rapid traffic growths,
urbanization and industrialization have contributed
significantly to economic growth, the heavy pollution
emissions created from manufacturing facilities, major
industrial zones, a dramatic increase in the number of
residences , office buildings, and increase in the number of
motor vehicles (Cohen, 2006).
It is important to record and observe the changes
of gases to understand and evaluate their impact on
climate change and to obtain more reliable and longer
range projections. The abundances of the atmosphere
gases, last few decades, were obtained from different
sources by sparsely distributed measurements sites,
Balloons and airplanes. These observations are more
sensitive to sources and mostly limited to the surface. And
major shortfall is not able to have continuously daily
global variations evolutions (Rajab et al., 2009). The
IRAQ as developing countries, have inadequate
mechanism to monitor such emissions due to involvement
of high cost in spread out the ground monitoring networks.
Only observations from the space by satellite
remote sensing allows for such measurements, which has
good global coverage increase our ability to access the
impact of human activities on the climate change and
GHG's. The in-situ measurements have poor spatial
coverage compared to satellite measurements surface, but
are more precise and less subject to biases (Wang et al.,
2016).
The CH4 spatiotemporal distributions and
variations from satellite measurements used in several
studies for different regions, which provide some
information and evidence for its sources and traces in the
atmosphere (Mahmood et al., 2016, Rajab et al., 2012,
Zhang et al., 2011). Xiong et al (Xiong et al., 2013)
selected the strong AIRS CH4 channels near 1306 Cm-1to
detect methane depletion associated with the stratosphere
intrusion , they suggested that AIRS and /or other thermal
sounders can provide an observations of CH4 variation
associated with stratosphere intrusion. Xiong et al (Xiong
et al., 2009) studied methane plume over south Asia
during monsoon season using AIRS data the period from
2003-2007, results shows a strong plume-like
enhancement of CH4 in the middle to upper troposphere
over Asia.
This study is designed to map the spatiotemporal
distribution patterns and trend of tropospheric CH4 for the
period 2003-2015 over IRAQ using the retrieved AIRS
level 3 monthly products (AIRX3STM) and daily product
(AIRX3STD) version 6 data. The results help in identify
and analysis the hotspots for regional CH4 emissions over
study area. The CH4 satellite data were evaluated over
three stations; Mosul, Baghdad and Basrah respectively,
the monthly mean CH4 were generated using Kriging
interpolation technique to analyze its distribution for the
study area.
STUDY AREA
Iraq is one of the southern west Asia countries.
Lies between (39o- 49o E) longitudes and (29o-38o N)
latitude, comprises of 437,376 square kilometers and it is
the 58th - largest country in the world (Figure-1). It is
bordered by Turkey to the north, Iran to the east, Saudi
Arabia and Kuwait to the south, and Jordan and Syria to
the west. Topographically, Iraq is formed as a basin and
divided into four major regions: alluvial plain in central
and southeast sections; highlands in north and northeast;
rolling upland between upper Tigris and Euphrates rivers;
and desert in west and southwest. These two major rivers
run through the centre of Iraq, flowing from northwest to
southeast are fertile alluvial plains, which covers 19,425
square kilometers of marshland at south-eastern of Iraq.
The Desert regions at south and west constitute half of
Iraq. Mountains form most northern parts, the highest
point being at 3,611 m (11,847 ft). Iraq has a narrow
section of coastline measuring 58 km (36 mi) on the
northern Arab Gulf (Activity, 1998).
The Iraq climate is continental, subtropical and
semi-arid, and most parts have a hot arid climate with
subtropical influence. Mountain region, the north and
northeastern parts, are having a Mediterranean climate.
The precipitation is low, the maximum rainfall happen
during winter, and it's extremely rare during the summer.
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Figure-1.Study area Iraq and the main stations.
The mean annual rainfall about 216 mm and most
places receive less than 250 mm. The winter is cool season
and its temperatures infrequently exceed 21 °C and night-
time lows 2 °C. Temperatures are colder at northern
regions and have occasional heavy snows, sometimes
causing extensive flooding. The summer is dry and hot
season, and the shade temperature average above 40 °C
daytimes for most of the country, frequently exceed 48 °C,
and drops to 26 °C at nights. Summer months are
prevailing by shamal winds; it is steady wind and blows
from north and northeast (Frenken, 2009, Metz, 1990).
DATA ACQUISITION AND METHODOLOGY
Recently, the space-borne remote sensing has
employed to measure CH4 with the large spatial and
temporal coverage, which can effectively compensate the
lack of surface observations measurements. The AIRS,
thermal infrared sounders, is one of several instruments
was launched aboard NASAs EOS Aqua platform at a
705 Km -altitude, polar orbit, on 4 May 2002. Its Equator
crossing time is 01:30/13:30, with global coverage due to
a 1650 km cross track scanning swath, and spatial
resolution field-of-view (FOV) is 13.5 km at nadir. In a
24-h period AIRS nominally observes the complete globe
twice per day (Xiong et al., 2008). With 2378 channels at
high spectral resolution (λ/ λ =1200) and low noise, the
AIRS covering from 6491136, 12171613 and 2169-
2674 Cm-1(Aumann et al., 2003).
AIRS Version 6- L3 is providing three products:
daily, 8-day and monthly (total column) each product
provides separate ascending (daytime) and descending
(nighttime) besides 24 Standard Pressure Levels for
volume mixing ratio (VMR). Level 3 files contain
geophysical parameters that have been averaged and
binned into 1°x1° grid cells. Grid maps coordinates range
from -180.0° to +180.0° in longitude and from -90.0° to
+90.0° in latitude (Olsen et al., 2007). There are about 200
AIRS channels spanning the 7.66µm CH4 absorption
bands, about 70 AIRS channels used for the CH4 retrieval,
and the surface temperature, atmospheric temperature
profile, water profile and surface emissivity demanded as
inputs are derived from other AIRS channels (Xiong et al.,
2008).
AIRS standard CH4 products are derived from the
IR stage of the combined IR/MW retrieval. This study was
used effective CH4 total column (CH4) (Mole.Cm-2).
Generally, 156 monthly L3 ascending granules were
AIRX3STM version 6 (V6) product's files from the AIRS
website, and saves in HDF-EOS4 files, which is a
convenient file extension can be easily take out data from
it and arrange in table using MS Excel. The monthly data
basis including the corresponding time and location along
the satellite track were in a Hierarchical Data Format
(HDF) format.
Map of the study area was conducted by using
geographic information system (GIS) software to analyze
the CH4 data distribution along the study period. The CH4
data were obtained from 1° × 1° (latitude × longitude)
spatial resolution ascending orbits. The percentage change
also used, which is a method gives a more precise
description as how the data has changed over a period of
time; it is describe the change as a percentage of previous
value. This method was applied between two years 2003
and 2015 for monthly CH4 values- total column (Bennett
et al., 2008).
The Regression analysis is a technique to study
the connection (relationship) between a dependent variable
and one or several independent variables (Angelbratt et
al., 2011). In this paper we studied the relationship
between the independent variable (time) and the dependent
variable (CH4, annually and monthly) over three
considered stations Mosul, Baghdad and Basrah. Also, the
daily long-term CH4 over Baghdad used to study and
estimate the daily time series of CH4 from 1 January 2003
till 31 December 2015. Furthermore, the moving average
and day to day variation method were applied for daily
CH4 data to get better overall idea of trend because of
these methods are useful for forecasting long term-trends.
RESULT AND DISCUSSIONS
Monthly analysis long- term CH4 data over Iraq
Figure-2 (a, b) illustrated the monthly mean CH4
total column over the study area from January 2003 to
December 2015. From CH4 values observed the spatial
variation over most parts of Iraq, minor differences in
spatial patterns for each season, and various seasonal
fluctuations depended on weather conditions and
topography. The lowest values were at pristine desert
environment in western and southwest regions, and over
mountainous areas at the north-east regions. The highest
values were at the central and southern-east parts of Iraq,
especially over Baghdad and Basrah during the study
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period. This is due to the many natural sources such as;
alluvial plain, agriculture, wetlands, salt marshes,
anthropogenic activities, and industrial emissions.
Figure-2 (a) shows that the lowest value
(3.083x1019) Mole.Cm-2 of CH4 throughout the year over
the study area occurred during the spring season (March -
May) at the pristine desert environment in western and
southwest regions. Also decrease over mountainous areas
at the north-east regions. Elevation in CH4 values (3.858
x1019) Mole.Cm-2 on March appeared from western north
of Baghdad to south east area till the Iraqi - Iran border, by
unit area, which is mostly connected to the increase in
temperature and the presence of water swamps. The mean
and slandered deviation of CH4 for spring was (3.483 ±
0.002 x1019) Mole.Cm-2 and the mean CH4 values in
Mosul, Baghdad and Basrah on April were (3.651, 3.800
and 3.837 x 1019) Mole.Cm-2 respectively.
Figure-2a.Spring and summer mean monthly CH4 Spatial and temporal variation over Iraq
(March - August) 2003 - 2015.
The temperature is the dominant factor in
acceleration the CH4 concentration. The reduction of CH4
values during the year cycle due to the low air
temperature. In addition, during spring and summer
seasons in Iraq the most predominant prevailing is strong
northwesterly winds known as "shamal winds", which is
steady and blows from the north and northeast (low air
temperature). The winter Shamal events occur as
frequently as two to three times per month between
December and early March (Abdi Vishkaee et al., 2012).
Also, the prevalent sources of CH4 represented by
wetlands rather than the anthropogenic sources are mainly
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affected by temperature, which is comparatively mild in
Iraq during spring beside precipitation. The CH4 emissions
are decreases with decreases temperature (Nisbet et al.,
2016, Li et al., 2015).
A plainly evident and gradual increase in CH4
values during the summer season (June - August)
especially at the center and southeast areas along the
Tigris and Euphrates basin. And drop over desert and
mountainous areas. The highest values were (3.873x1019)
Mole.Cm-2 on June, and the lowest were (3.144 x 1019)
Mole.Cm-2 on August at late summer. In July CH4 for
Mosul, Baghdad and Basrah were (3.678, 3.814, and
3.808) x1019 Mole.Cm-2, respectively. The gradually
increases of CH4 emissions during summer compare to its
values in spring are due to increasing sunny hours leads to
increasing temperature, and Higher temperatures alone
would increase methane production in saturated areas
(Akumu et al., 2010).
Figure-2b.Autumn and winter mean monthly CH4 spatial and temporal variation over Iraq
(September - February) 2003 - 2015.
Figure-2 (b) illustrated the CH4 distributions
during autumn and winter seasons (September - February).
At autumn (September - November) the highest CH4 value
was (3.894x1019) Mole.Cm-2 particularly on September.
The lowest CH4 value through this entire period was
(3.161 x 1019) Mole.Cm-2. The mean CH4 values in
Mosul, Baghdad and Basrah on October were (3.695,
3.843 and 3.884) x1019 Mole.Cm-2, respectively. Normally
the late autumn concurs with minimum OH levels. In
additions, the CH4 emissions in different regions of Iraq
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affects by the instability of the climatic conditions with
subtropical anticyclones importantly. Therefore, CH4
fluxes have significant enhancement in the late autumn
and early winter seasons due to reductions in OH, which
formed from water vapor collapse by O2 atoms that come
from the cleaving of O3 by UV radiations (Rajab et al.,
2012, Langenfelds et al., 2002).
During winter, the minimum CH4 values were at
western, southwest and north-east regions, and the
maximum values were at the central and southern-east
regions. The highest CH4 value in December was
(3.909x1019) Mole.Cm-2, and the lowest was in February
(3.143x1019) Mole.Cm-2. The mean and slandered
deviation CH4 values throughout the winter was (3.512 ±
0.041x1019) Mole.Cm-2, and its values for Mosul,
Baghdad and Basrah in January were (3.669, 3.842 and
3.860) x1019 Mole.Cm-2 respectively. Observed lowest
values of CH4 in the northern region than southern at
winter season due to the shorter days, few sunny hours,
and low temperatures during the winter. Furthermore,
because of the maximum precipitation occurred, rain is a
great cleanser of gases from the atmosphere because of
their solubility (Hoskins, 2001), and the lack of rice
cultivation during the winter season also contributes to
reduction in CH4 emissions.
Percentage change analysis long- term CH4 data
The CH4 total column measurements from AIRS
for two months (January and October) were selected to
investigate the percentage change method. Also, a direct
comparison of the CH4 is straightforward with the use of
mapping. Figure 3 illustrate the maps of Iraq for the CH4in
January and October during 2015 (top), 2003 (middle),
and the percentage change between the two measurements
(2015 - 2003, bottom). The spatial distribution patterns of
CH4 maps for percentage change method (Figure-3
bottom) shows high variation and significant differences.
In January, the difference for CH4 values between
2015 and 2003 ranges from 0.023 to 0.0395 in most areas,
in the north less than the south and in the west less than
the east. The greatest differences were in the south regions
(0.036 - 0.0395) over Basrah. And the west and north
regions had a less difference (0.023 - 0.027) than the rest
of the areas. The highest differences were at southern area
0.0395, whereas the lowest in the northern area 0.023 and
at Mosul, Baghdad and Basrah were 0.0253, 0.0335 and
0.0394, respectively.
For October, the differences ranged from 0.018 to
0.034, and the west regions still had the smallest
difference, while the greatest difference was on the south
due to the expansion and proliferation of rice farms and
increased production of oil fields. The maximum
difference was (0.034) whereas the minimum was (0.018)
and at Mosul, Baghdad and Basrah were 0.0262, 0.0259
and 0.0277, respectively.
We can deduce from the percentage change
differences (Figure-3 bottom) that the highest differences
occurred over agriculture, wetlands, salt marshes,
industrial and congested urban zones, usually in the central
and southern regions when CH4 values were high. The
smallest differences CH4 values, between 2015 and 2003,
occurred in the pristine desert environment in western and
southwest regions.
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Figure-3.The percentage change of CH4 values between October and January 2003 and 2015.
Trend analysis
Annually long - term CH4 data trend
To evaluate the annual mean CH4 total column
over the study area, we selected three sites across Iraq:
Mosul, Baghdad and Basrah. Figure-4, show the annually
CH4 from 2003 to 2015 for these three cities. The mean
and standard deviation was (3.751± 0.108) x 1019
Mole.Cm-2 for an entire period shows CH4 experience
various seasonal fluctuations depending on weather
conditions and topography. There is a progressive increase
in the CH4 values with prominent growth rate variations
observed during the 2003-2015 period. An increasing,
long-term trend in CH4 can be attributed to the increase of
human activities and anthropogenic emissions.
In addition, the observed atmospheric increase of
CH4 due to the combination of decreasing sinks and
increasing sources. If OH radicals are depleted in the
troposphere, the Atmospheric CH4 may increase. Such
depletion could occur from the growing industrial
activities of carbon monoxide (CO) levels. The change of
OH,CO, and CH4 are coupled together at the long term,
thus possible slow decrease of OH levels may add to the
rate of rise CH4(Khalil and Rasmussen, 1983).
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Figure-4. Annually CH4 values (2003-2015) over Mosul, Baghdad and Basrah.
The maximum annual CH4 was 3.887x1019
Mole.Cm-2 over Basrah in 2015, and the minimum was
3.568 x1019 Mole.Cm-2 over Mosul in 2003. The linear
growth rate for each station was (2%) for Mosul, and (3%)
for Baghdad and Basrah, (this percentage value is with
respect to the mean Value). The annual trend analysis
shows positive trends (i.e. increasing CH4 concentration is
associated with increasing years). This results shown in
Table-1, and ranged between (0.0083 and 0.0097)
Mole.Cm-2.y-1 for Mosul and Basrah, respectively.
Table-1. The locations, Annual mean CH4, Maximum, Minimum, and Trend of CH4 for the period (2003-2015).
Station
Latitud
e
(Nº)
Longitude
()
Mean of
Annual
CH4 x1019
(Mole/Cm2)
Maximum
CH4 x1019
(Mole/Cm2)
Minimum
CH4 x1019
(Mole/Cm2)
Standard
deviation
CH4 x1019
(Mole/Cm2)
Mosul
36.31
43.15
3.6106
3.6671
3.5680
0.0366
33.3
44.40
3.8184
3.8866
3.7702
0.0417
Basrah
30.52
47.78
3.8240
3.8872
3.7636
0.0428
Monthly long-term CH4 data trend
The mean monthly CH4 are presented in Figure-
5, which shows a graph of a monthly long series for mean
CH4 over Mosul, Baghdad and Basrah from January 2003
to December 2015. The CH4 experience various seasonal
fluctuations depending on weather condition and
topography, with minimum in March - May and maximum
at September. Observed a stagnation and stability feature
as obvious during 2003 until 2008, and began to ascend
again in 2009 after five years of near-zero growth. It might
be the stability of CH4 measurements during 2003-2008
include: a decrease in anthropogenic emissions,
decreasing-to stable fossil fuel emissions and coincident
with USA occupation of Iraq, which caused to stop all
industrial activities.
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Figure-5. The monthly CH4 value (2003-2015) over Mosul, Baghdad and Basrah.
The renewed increase of CH4 concentrations after
2009 could be suggested by few reasons such as; increased
renovation and reconstruction of war remnants, the
number of vehicles has doubled, increase of oil extraction
operations, and expansion of agricultural areas, especially
the paddies. Furthermore, because of the reduction in
(OH) radicals this is the main removal for many species,
beside CH4, such as CO, CO2 and NO2. These species are
resulting from different sources such as the oxidation
process of CH4 by OH radicals, which can be removed
later by OH radicals from the atmosphere, and its reactions
with OH are slowing down the CH4 removal process,
especially the reaction between CO and OH radicals. Also,
the significant reduction of OH due to the increasing in
anthropogenic emission of CO2 (from transport) coupled
with CO from CH4 Oxidation, which led to slowdown in
the rate of CH4 removal (Jardine et al., 2004).
The trend analysis of CH4 for these three cities
were estimated and had a positive trends (0.0092)
Mole.Cm-2.y-1 for Mosul and (0.0107) Mole. Cm-2.y-1 for
Baghdad and Basrah, as summarized in table 2. The linear
growth rates were (5%) for Mosul and Baghdad, and (6%)
for Basrah (growth rate is the percentage calculated with
respect to the mean). The mean and standard deviation for
the entire period was (3.751±0.11) x1019 Mole .Cm-2.
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Table-2. The locations, annual mean CH4, maximum, minimum, and trend of CH4 for the period (2003-2015).
Station
Latitude
()
Longitude
()
Annual
Mean CH4
x1019
(Mole/Cm2)
Maximum
CH4 x1019
(Mole/Cm2)
Minimum
CH4 x1019
(Mole/Cm2)
Standard
deviation
CH4 x1019
(Mole/Cm2)
Trend
CH4 x1019
Mole/Cm2.y-1
Mosul
36.31
43.15
3.6106
3.7087
3.5250
0.0425
0.0092
33.3
44.40
3.8184
3.9483
3.7240
0.0489
0.0107
Basrah
30.52
47.78
3.8240
3.9438
3.6921
0.0554
0.0107
Daily long - term data trend over Baghdad
Figure-6 (a-b), Show the daily CH4values and 12
point binomial smoothing in applied to daily CH4 values
(to reduce the complexity of variation) over Baghdad from
1 January 2003 to 31 December 2015. In spite of
important short term variation during study period, there is
exists a seasonal change with mean, maximum and
minimum of CH4 values [(3.81 ± 0.62), 4.06 and 3.54] ×
1019 Mole.Cm-2, respectively. The linear regression
analysis for daily measurements shows significant
enhancement about 0.139 × 1019 Mole.Cm-2 which
represents (3.7 % of the mean value) during the entire
period produced a positive trend (0.0107 × 1019) Mole.
Cm-2.y-1.
Figure-6 (a). Daily CH4 over Baghdad from 1 January 2003 to 31 December 2015; and
(b) 12 point smoothing in applied to daily CH4values.
The variation in daily average CH4 as a
percentage deviation from the mean (for 13 year daily
data) is shown in Figure-7. The maximum increase and
decrease daily variation in Baghdad were (6.2 %) (0.236
× 1019 Mole. Cm-2) and (- 7.2%) (- 0.274 × 1019)
Mole.Cm-2, and the standard deviation for the departure
from the mean was (1.62%), (0.06×1019 Mole.Cm-2).
Figure-8 presents the day to day variation with a clear
seasonal change, which shows enter sequential change of
time series in Figure-6. The maximum increase in the day
to day CH4 variation was (0.18 × 1019) Mole. Cm-2 and
minimum increase was (- 0.17 × 1019) Mole.Cm-2. The
standard deviation of enter sequential changes was (0.053
× 1019) Mole.Cm-2. (Ogunjobi, 2007).
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Figure-7.Variation of average CH4 expressed as percentage deviation from the meanover
Baghdad from 1 January 2003 to 31 December 2015.
Figure-8.Day to day CH4 variations at Baghdad city.
From the Figures 6 (a-b), 7 and 8, there is a
quasi-biennial variation in CH4 over Baghdad in
September is evident in the daily values with various
seasonal fluctuations. The significant increasing trend a
results of varying influences which include vertical
mixing, large scale dynamics and redistribution through
convection, advection of pollution with CH4 precursors,
the increase of anthropogenic emissions and human and
CONCLUSIONS
The GHGs concentration in the atmospheric has
increased due to continuous increases in anthropogenic
emissions resulting from increased industrialization,
analysis was undertaken of CH4 total column retrieved
from satellite data over Iraq using AIRS on EOS/Aqua
from January 2003 to December 2015. The high
concentrations of averaged CH4 column over Iraq are
mainly located in the regions of central and southern-east
parts. The significantly low concentrations are mainly
located in the pristine desert environment in western and
southwest regions, and over mountainous areas at the
north-east regions. There is a strong association between
CH4 concentration and human activity, but CH4
concentrations in the southern regions of Iraq not only are
affected by human activity but are clearly also caused by
agriculture, municipal solid waste, and natural gas and oil
extractions.
The transport effect is the reason that CH4
concentration is higher in the crowded cities, especially
over Baghdad and Basrah. The seasonal fluctuations of the
CH4 plume are observed by AIRS with maximum in
September and minimum in March - May. These results
indicate that AIRS observations contain significant
information about the CH4 distributions over different
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8661
regions. Therefore, AIRS CH4 product may be valuable
for studying at variance weather conditions and
topography.
From percentage change differences results
between 2015 and 2003, its values in January (0.023 -
0.0395) more than in October (0.018 - 0.034), and the
highest differences occurred over the central and southern
regions when CH4 values were high. The smallest
differences CH4 values occurred in the pristine desert
environment in western and southwest regions. To better
validate the retrieved CH4 data from AIRS, three surface
stations at different locations and with various elevations
were chosen; Baghdad, Mosul and Basrah. The mean and
standard deviation was 3.751± 0.108) x1019 Mole.Cm-2 for
annual long term trend analysis. The linear growth rate for
each station was (2%) for Mosul, and (3%) for Baghdad
and Basrah. The annual trend analysis shows positive
trends, and ranged between (0.0083 and 0.0097) Mole.
Cm-2.y-1 for Mosul and Basrah, respectively.
The study further estimated a monthly trend
analysis with positive trends (0.0092) Mole. Cm-2.y-1 for
Mosul and (0.0107) Mole. Cm-2.y-1 for Baghdad and
Basrah. The mean standard deviation for the entire period
was (3.751±0.11) x1019 Mole.Cm-2. The linear growth
rates were (5%) for Mosul and Baghdad, and (6%) for
Basrah. The daily long term trend shows significant linear
increase of (3.7 %) caused a trend of (0.0107 × 1019)
Mole. Cm-2.y-1 in Baghdad. There is exists a seasonal
change for CH4 values and 12 point binomial. The
variation in daily average CH4 as a percentage deviation
from the mean shows standard deviation for the departure
from the mean was (1.62%), (0.06×1019 Mole.Cm-2). And
the day to day variation with a clear seasonal change
shows standard deviation of enter sequential changes was
(0.053 × 1019) Mole.Cm-2.
The trends are assumed to be due to the reduction
in (OH) radicals this is the main removal for many species,
beside CH4, such as CO, CO2 and NO2. In addition,
increased the human activities and oil extraction
operations, the number of vehicles has doubled, and
expansion of agricultural areas, especially the paddies. The
Satellite results efficiently show the temporal variations of
show a good consistency for the contrasted seasonal
analysis results. The AIRS data and satellite measurements
can be used to measure the increases of the atmosphere
CH4 values over different area.
ACKNOWLEDGEMENT
The authors gratefully acknowledge the National
Aeronautics and Space Administration (NASA) Goddard
Earth Sciences Data Information and Services Centre
(DISC) for the provision of the AIRS data and images
used in this paper.
REFERENCES
Abdi Vishkaee F., Flamant C., Cuesta J., Oolman L.,
Flamant P. & Khalesifard H. R. 2012. Dust transport over
Iraq and northwest Iran associated with winter Shamal: A
case study. Journal of Geophysical Research:
Atmospheres. 117.
Activity, U. S. M. C. I. 1998. Iraq Country Handbook,
Marine Corps Intelligence Activity.
Akumu, C. E., Pathirana, S., Baban, S. & Bucher, D. 2010.
Modeling methane emission from wetlands in North-
Eastern New South Wales, Australia using Landsat ETM+.
Remote Sensing, 2, 1378-1399.
Angelbratt J., Mellqvist J., Blumenstock T., Borsdorff T.,
Brohede S., Duchatelet P., Forster F., Hase F., Mahieu E.
& Murtagh D. 2011. A new method to detect long term
trends of methane (CH 4) and nitrous oxide (N 2 O) total
columns measured within the NDACC ground-based high
resolution solar FTIR network. Atmospheric Chemistry
and Physics. 11, 6167-6183.
Atique L., Mahmood I. & Atique F. 2014. Disturbances in
atmospheric radiative balance due to anthropogenic
activities and its implications for climate change. system,
6, 2.
Aumann H. H., Chahine M. T., Gautier C., Goldberg M.
D., Kalnay E., Mcmillin L. M., Revercomb H.,
Rosenkranz P. W., Smith W. L. & Staelin D. H. 2003.
AIRS/AMSU/HSB on the Aqua mission: Design, science
objectives, data products, and processing systems. IEEE
Transactions on Geoscience and Remote Sensing, 41, 253-
264.
Bartlett K. B. & Harriss R. C. 1993. Review and
assessment of methane emissions from wetlands.
Chemosphere, 26, 261-320.
Bennett J. O., Briggs W. L. & Badalamenti A. 2008. Using
and understanding mathematics: A quantitative reasoning
Bergamaschi P., Houweling S., Segers A., Krol M.,
Frankenberg C., Scheepmaker R., Dlugokencky E., Wofsy
S., Kort E. & Sweeney C. 2013. Atmospheric CH4 in the
first decade of the 21st century: Inverse modeling analysis
using SCIAMACHY satellite retrievals and NOAA
surface measurements. Journal of Geophysical Research:
Atmospheres. 118, 7350-7369.
Bernstein L., Bosch P., Canziani O., Chen Z., CHRIST R.
& Riahi K. 2008. IPCC, 2007: climate change 2007:
synthesis report. IPCC.
Blais A. & Lorrain S. 2005. Greenhouse gas fluxes (CO 2,
CH 4 and N 2 O) in forests and wetlands of boreal,
temperate and tropical regions. In Greenhouse gas
emissions-fluxes and processes.(Eds A Tremblay, L
Varfalvy, C Roehm, M Garneau) pp. 87-127. Springer-
Verlang: Berlin.
VOL. 13, NO. 22, NOVEMBER 2018 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
www.arpnjournals.com
8662
Bousquet P., Ciais P., Miller J., Dlugokencky E.,
Hauglustaine D., Prigent C., Van Der Werf G., Peylin P.,
Brunke E.-G. & Carouge C. 2006. Contribution of
anthropogenic and natural sources to atmospheric methane
variability. Nature. 443, 439.
Cohen B. 2006. Urbanization in developing countries:
Current trends, future projections, and key challenges for
sustainability. Technology in society, 28, 63-80.
Dlugokencky E., Bruhwiler L., White J., Emmons L.,
Novelli P. C., Montzka S. A., Masarie K. A., Lang P. M.,
Crotwell A. & Miller J. B. 2009. Observational constraints
on recent increases in the atmospheric CH4 burden.
Geophysical Research Letters. 36.
Frenken K. 2009. Irrigation in the Middle East region in
figures AQUASTAT Survey-2008. Water Reports.
Hausmann P., Sussmann R& Smale D. 2016. Contribution
of oil and natural gas production to renewed increase in
atmospheric methane (2007-2014): topdown estimate
from ethane and methane column observations.
Atmospheric Chemistry and Physics. 16, 3227-3244.
Hoskins J. A. 2001. Ozone matters. Indoor and Built
Environment. 10, 1-2.
Jardine C. N., Boardman B., Osman A., Vowles J. &
Palmer J. 2004. Methane UK. The environmental change
institute.
Jasim M., Matjafri M., Lim H. & Abdullah K. 2010. Daily
distribution map of ozone (O3) from AIRS over Southeast
Asia. Ener Res J. 1, 158-164.
Kai F. M., Tyler S. C., Randerson J. T. & Blake D. R.
2011. Reduced methane growth rate explained by
decreased Northern Hemisphere microbial sources.
Nature. 476, 194-197.
Khalil M. & Rasmussen R. 1983. Sources, sinks, and
seasonal cycles of atmospheric methane. Journal of
Geophysical Research: Oceans. 88, 5131-5144.
Kirschke S., Bousquet P., Ciais P., Saunois M., Canadell J.
G., Dlugokencky E. J., Bergamaschi P., Bergmann D.,
Blake D. R. & Bruhwiler L. 2013. Three decades of global
methane sources and sinks. Nature Geoscience, 6, 813.
Kreft S., Eckstein D., Dorsch L. & Fischer L. 2015. Global
climate risk index 2016: who suffers most from extreme
weather events? weather-related loss events in 2014 and
1995 to 2014, Germanwatch Nord-Süd Initiative eV.
Lagzi I., Meszaros R., Gelybo G. & Leelossy, A. 2014.
Atmospheric chemistry.
Langenfelds R., Francey R., Pak B., Steele L., Lloyd J.,
Trudinger C. & Allison C. 2002. Interannual growth rate
variations of atmospheric CO2 and its δ13C, H2, CH4, and
CO between 1992 and 1999 linked to biomass burning.
Global Biogeochemical Cycles. 16.
Li T., Zhang W., Zhang Q., Lu Y., Wang G., Niu Z.,
Raivonen M. & Vesala T. 2015. Impacts of climate and
reclamation on temporal variations in CH 4 emissions
from different wetlands in China: from 1950 to 2010.
Biogeosciences. 12, 6853-6868.
Mahmood I., Iqbal M. F., Shahzad M. I., Waqas A. &
Atique L. 2016. Spatiotemporal monitoring of CO2 and
CH4 over Pakistan using Atmospheric Infrared Sounder
(AIRS). International Letters of Natural Sciences. 58.
Melling L., Hatano R. & Goh K. J. 2005. Methane fluxes
from three ecosystems in tropical peatland of Sarawak,
Malaysia. Soil Biology and Biochemistry. 37, 1445-1453.
Metz H. C. Iraq: A Country Study: Research Completed
May 1988. 1990. Federal Research Division, Library of
Congress.
Nisbet E., Dlugokencky E., Manning M., Lowry D., fisher
R., France J., Miche S., Miller J., White J. & Vaughn B.
2016. Rising atmospheric methane: 20072014 growth
and isotopic shift. Global Biogeochemical Cycles. 30,
1356-1370.
Ogunjobi K. 2007. Temporal and spatial patterns of
interannual variability of total column ozone in Africa
from ground-based observations. Research Journal of
Applied Sciences. 2, 666-672.
Olsen E. T., Granger S., Manning E. & Blaisdell J. 2007.
AIRS/AMSU/HSB Version 5 level 3 quick start. Jet
Propulsion Laboratory California Institute of Technology,
Pachauri R. K., Allen M. R., Barros V. R., Broome J.,
Cramer W., Christ R., Church J. A., Clarke L., Dahe Q. &
Dasgupta P. 2014. Climate change 2014: synthesis report.
Contribution of Working Groups I, II and III to the fifth
assessment report of the Intergovernmental Panel on
Climate Change, IPCC.
Rajab J. M., Matjafri M. & Lim H. 2012. Methane
interannual distribution over Peninsular Malaysia from
atmospheric infrared sounder data: 2003-2009. Aerosol
and Air Quality Research. 12, 1459-1466.
Rajab J. M., Matjafri M., Lim H. & Abdullah K. 2009.
Satellite mapping of CO2 emission from forest fires in
Indonesia using AIRS measurements. Modern Applied
Science. 3, 68.
Schaefer H., Fletcher S. E. M., Veidt C., Lassey K. R.,
Brailsford G. W., Bromley T. M., Dlugokencky E. J.,
Michel S. E., Miller J. B. & Levin I. 2016. A 21st-century
VOL. 13, NO. 22, NOVEMBER 2018 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
www.arpnjournals.com
8663
shift from fossil-fuel to biogenic methane emissions
indicated by 13CH4. Science. 352, 80-84.
Spahni R., Wania R., Neef L., Weele M. V., Pison I.,
Bousquet P., Frankenberg C., Foster P., Joos F. &
PRENTICE I. 2011. Constraining global methane
emissions and uptake by ecosystems. Biogeosciences. 8,
1643-1665.
Wang Z., Warneke T., Deutscher N., Notholt J., Karstens
U., Saunois M., Schneider M., Sussmann R., Sembhi H. &
Griffith D. W. 2016. Contributions of the troposphere and
stratosphere to CH4 model biases. Atmospheric Chemistry
and Physics Discussions.
Wuebbles D. J. & Hayhoe K. 2002. Atmospheric methane
and global change. Earth-Science Reviews. 57, 177-210.
Xiong X., Barnet C., Maddy E., Sweeney C., Liu X., Zhou
L. & Goldberg M. 2008. Characterization and validation
of methane products from the Atmospheric Infrared
Sounder (AIRS). Journal of Geophysical Research:
Biogeosciences. 113.
Xiong X., Barnet C., Maddy E., Wofsy S., Chen L.,
Karion A. & Sweeney C. 2013. Detection of methane
depletion associated with stratospheric intrusion by
atmospheric infrared sounder (AIRS). Geophysical
Research Letters. 40, 2455-2459.
Xiong X., Houweling S., Wei J., Maddy E., Sun, F. &
Barnet C. 2009. Methane plume over south Asia during
the monsoon season: satellite observation and model
simulation. Atmospheric chemistry and physics. 9, 783-
794.
Zhang X., Bai W., Zhang P. & Wang W. 2011.
Spatiotemporal variations in mid-upper tropospheric
methane over China from satellite observations. Chinese
science bulletin. 56, 3321-3327.
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