INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 5
Carbon Dioxide (CO
2
) Emission on Agricultural Land Use and its
Impact on food Production
*
Awe B.S., Olutomilola A.O. and Oluwatobi O.B.
Department of Agricultural and Bio-Environmental Engineering
*
Corresponding Author
DOI: https://doi.org/10.51583/IJLTEMAS.2024.130702
Received: 13 June 2024; Revised: 29 June 2024; Accepted: 03 July 2024; Published: 26 July 2024
Abstract: The study assesses Carbon dioxide emissions from agricultural land use which have a great impact on food production
and atmospheric weather. Emissions of CO
2
from the land use surface lead to minimum production of farm products. Global
warming and climate change are the cause of great concern, demanding intensive research on CO
2
emissions from soil under
some management options. The aim is to determine CO2 emission on agricultural land use with food security. An experiment
was conducted using sodium hydroxide as a reagent for the emission, the results obtained demonstrated that the highest CO
2
emission was observed in maize farm which is 6.0 g CO
2
m
-2
d
-1
and the least was found in yam farm and forest location which
are 0.5g CO
2
m
-2
d
-1
, at a point where the soil moisture was maximum (23.5%), the soil pH was minimum (4.84), the total organic
carbon (TOC) storage in the soil was maximum (1.7%), then the CO
2
emission was low in a forest location because
mineralization of soil bacteria’s is not active in moist soil they are very active in a soil that lacks moisture, and bacteria contribute
to the emission of carbon dioxide due to their activities in the soil.
Keywords: carbon dioxide emissions, global warming, climate change, soil bacteria, and soil moisture
I. Introduction
The distribution of CO
2
between the atmosphere and the soil is caused by the respiration of the soil and plant photosynthesis; the
respiration of soil microorganisms and plant roots produces carbon dioxide emission in the soil. It is widely known that about
70% of soil CO
2
emissions are caused by soil microbial respiration [9] According to most researchers, the place of respiration of
soil microorganisms on plant roots in all soil depends on hydrothermal conditions [8]. Soil respiration means the production of
carbon dioxide when the soil is in an unopened mode.
In recent years, soil carbon dioxide production has been the subject of intense studies because the rate at which emissions occur
depends on land use and land management systems, which include forestry, upland agriculture, paddy rice, and animal husbandry.
Other factors influencing soil CO
2
production rate include atmosphere temperature, moisture, root respiration, microbial
processes, soil aeration, porosity, and water [3].
Many years ago, most tropical countries, such as Ghana, considered themselves to be net anecdotal assertions based on the low
level of industries in the countries. In the coming decades, a large reduction of carbon dioxide emissions will be required to
mitigate climate change. The extent of emission rate lowering is needed to stabilize atmospheric carbon dioxide concentrations,
and the inertia involved in rotating the world’s primary energy sources from fossil fuels to other alternatives, carbon capture and
storage (CCS), will likely contribute to a substantial share of the reduction in emissions in the next half-century. Previous
research has made it clear that air capture is theoretically feasible in terms of thermodynamic energy requirements [10].
Temperature and precipitation are the most common and most significant factors influencing soil organic carbon (SOC) dynamics
[2]. The increase in temperature may lead to an increase in plant production, therefore increasing carbon inputs to the soil which
also tends to increase microbial decomposition of SOC [11]. There is strong empirical support for the idea that increasing in earth
temperature will cause the net loss of soil carbon to the atmosphere. Also with climate change more common excessive rainfall
and scarcity events are projected which may have greater impacts on ecosystem activity than the singular or combined effects of
rising CO
2
and temperature [6]. This increase may aggravate the rate and sensitivity to quick erosion and other degradation
processes leading to further carbon losses. Lastly, climatic change can affect several soil-forming factors including rainfall,
vegetation, temperature, and microorganisms which badly affect the rate of soil organic carbon accumulation due to climate
change. Drylands are expected to expand while SOC stock is likely to be reduced.
Carbon dioxide emissions from agricultural land use have created a low production of farm products and an increase in heat
radiation. This low production of farm products occurs when the carbon dioxide that plants need for their photosynthesis escapes
to the atmosphere, CO
2
escapes to the air by burning fossil fuels, felling of forestry trees (deforestation), and other human
activities. Carbon dioxide (CO2) poses a significant threat to global climate change mitigation efforts [4]. Recent studies have
highlighted the need for accurate quantification and understanding of the dynamics of CO2 emissions from different agricultural
land uses, which is crucial for developing effective climate-smart agriculture strategies [12].
Forests are invaluable to all life on Earth and cover one-third of the total land area. It contains most of the world's terrestrial
biodiversity, and 1.6 billion people look to it as their source of livelihood. According to [7], forests cover up to 4.03 billion
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 6
hectares nearly 30 percent of the earth’s surface. Mostly soil carbon is concentrated in forest land, therefore forests must be
sustainably managed to reduce the act of land degradation and deforestation because large amounts of CO
2
are emitted when
converting forests to agricultural land use such as maize farming, yam farming, and others. Soil management and land use can
contribute to the reduction in CO
2
emissions and also lower its concentration in the air by stopping deforestation to preserve the
current carbon reservoirs, and enlarge living terrestrial carbon reservoirs through reforestation [1].
Food security concerning climate change is affected in four various dimensions [3], which are: food availability, food
accessibility, stability of food supply, and ability of consumers to adequately utilize the food (food safety and nutrition). There is
a way to prevent this emission of CO
2
from the land by avoiding deforestation, burning fossil fuels, and other human activities
that may likely lead to the emission, for a better farming system to end hunger, adapt to, achieve overall sustainable development,
and control climate [5].
II. Materials and Methods
Description of the Site
The study was conducted at four locations, which were: maize farm, lied between longitudes 7
0
35’ 15’’ N and latitudes 5
0
17’
50’’ E; yam farm, lied between longitudes 7
0
36’ 7.56’’ N and latitudes 5
0
17’ 27.4’’ E; forest area, lied between longitudes 8
0
60’
21’’ N and latitudes 6
0
29’ 09’’ E; and cattle ranch, lied between longitudes 7
0
15’ 35.4’’ N and latitudes 5
0
11’ 46.2’’ E within
the Federal Polytechnic Ado-Ekiti, Ekiti State.
Reconnaissance survey
A reconnaissance survey was carried out at each location to have an intensive knowledge of the site. The study took place at four
locations which are; maize farm, yam farm, forest area, and cattle ranch area within The Federal Polytechnic Ado–Ekiti, Ekiti
State.
Experimental Procedure
i. Maize farm: lies between longitudes 7
0
35’ 15’’ N and latitudes 5
0
17’ 50’’ E. The farm was subdivided into four parts (fig. 1)
where the box was installed, the vegetation in this area are tall grasses.
Figure 1: Maize farm
ii. Yam farm: lies between longitudes 7
0
36’ 7.56’ N and latitudes 5
0
17’ 27.4’’ E. The farm was subdivided into four parts (fig.
2) where the box was installed, the vegetation in this area are mixture of grasses and scattered tree.
Figure 2: Yam farm
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 7
iii. Forest area: lies between longitudes 8
0
60’ 21’’ N and latitudes 6
0
29’ 09’’ E. The area was also subdivided into four parts
(fig. 3), the vegetation type in this location are tall trees and short grasses.
Figure 3: Forest area
iv. Cattle ranch area: lies between longitudes 7
0
15’ 35.4’’ N and latitudes 5
0
11’46.2’’ E. The location was subdivided into four
parts (fig. 4) where the boxes were installed, the vegetation in this area are mixture of stubborn grass and elephant grass.
Figure 4: Cattle ranch area
Carbon Dioxide Emission Determination
Sodium hydroxide was used as a reagent. First, the empty ceramic dishes were weighed on a weighing balance and recorded to be
w
1
, and a specific quantity of sodium hydroxide was put into the dish and weighed to be w
2.
Immediately, it was placed on the
land and covered for 24 hours, with the prepared box made of plywood closed. After 24 hours, it was reweighed and recorded to
be w
3
. The increase in weight of the sodium hydroxide is the carbon dioxide that escaped according to this reaction:
When sodium reacts with carbon dioxide, it gives sodium hydrocarbonate.
NaoH + Co
2
= NaHCo
3
When reacting with water
NaHCo
3
+ NaoH Na
2
Co
3
+H
2
o
2NaoH + Co
2
Na
2
Co
3
+ H
2
o
Laboratory Analysis
Soil samples were taken from each location and labeled, then examined to remove the roots, leaves, and unwanted materials, after
which they were taken to the laboratory to carry out the following analyses: bulk density, soil moisture content, soil pH, soil
particle size analysis, and soil organic carbon. Two trials were achieved at each location, and the average was determined except
for soil organic carbon.
Bulk density
The empty core sampler was weighed on the weighing balance and recorded to be w
1
. After that, it was inserted into the soil at
the location site and reweighed again to be w
2
. To get the mass of the soil, w
2
was subtracted from w
1
. For the volume, the height
and diameter of the core sampler were measured (height of 5 cm and diameter of 4.5 cm) to calculate the volume.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 8
Bulk density (kg/m
3
) =
Moisture content
The empty moisture can was cleaned and weighed to be 0.01 g (w
1
), then 100 grams of soil sample were placed into the can and
reweighed to be w
2
. The can with the soil sample was placed inside the oven and dried for 24 hours at a temperature of 105
o
C.
After that, the content was removed from the oven and placed inside the desiccators to allow it to cool, and after that, it was
weighed to be w
3
.
Moisture content (mc %) = (2)
Where: W
1
is the weight of empty moisture can
W
2
is the weight of moisture can + the wet soil sample
W
3
is the weight of moisture can + oven-dried soil sample.
Soil pH
First, the soil sample was sun-dried before being taken to the laboratory. 20 grams of soil samples from the dried soil were
weighed and poured into a 250-ml beaker. 40 ml of distilled water was added to the content and stirred until well mixed, then left
for 30 minutes to allow the suspension to settle. After that, the pH meter was calibrated with pH buffer solutions, and the probe of
the pH meter was inserted into the content without touching the soil in the beaker. The pH value for the soil was obtained after the
pH meter stopped reading.
Soil particle size analysis.
The weight of each sieve was noted and written down, including the receiver pan. All the sieves were thoroughly cleaned and
carefully arranged in ascending order from the receiver pan to 0.075mm and to the highest, which is 9.5mm. A specific quantity
of dried soil sample was carefully poured into the top sieve and covered. The arranged sieve stack was placed in the mechanical
shaker and it was shaken for 10 minutes. After that, the stack was carefully removed from the shaker. The remaining soil inside
each sieve was weighed and recorded as weight retained, and the soil in the receiver pan was weighed.
Soil organic carbon estimation
The wet oxidation method was used to estimate soil organic carbon. First, the soil sample was sun-dried for one week and it was
sieved to remove unwanted debris from it, 0.5g of the sieved soil was weighed on the weighing balance and poured into a conical
flask, 10ml of chromate was added and 20ml of sulphuric acid (H
2
SO
4
) was also added then shaken together, this was done for
each sample, the blank was prepared by adding chromate and H
2
SO
4
without soil, the content was left for 30minutes then 200ml
of water was added to dilute the acid, 5ml of phosphoric acid and little quantity of sodium chloride (Na
+
) was added to each
sample including the blank, phenylanine indicator was also added to the samples, ammonium ferrous sulphate was poured into the
burette then each sample was titrated until the color change and the reading was taken for the calculation.
Total Organic Carbon (TOC) = (3)
M = (4)
Where M is the total mass of titration.
III. Result and Discussion
Table 1 and Figure 5 depict the average CO2 emission measured in the different land use in the study area and it was observed
that maize farms emit more CO2 than other Agricultural land use while Yam and Forest have the same value (0.50 gco2m
-2
d
-1
).
The lands with the highest emissions were caused by the activities of humans and animals on the land such as deforestation,
overgrazing of the land, over tillage operation, bush burning and others, the land use with the lowest emission was not disturbed
by such activities.
Table 1: Average CO
2
Emission in Agricultural Land Use
Land use
Average Co
2
Emission (gco
2
m
-2
d
-1
)
Maize Farm
6.00
Cattle Ranch
4.25
Yam Farm
0.50
Forest
0.50
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 9
Figure 5: Graph showing the relationship between CO
2
emission and land use
Table 2 depicts Soil parameters and CO
2
emission, it was observed that soil Moisture content and Bulk density have a greater
impact on CO2 emission, the higher the moisture and bulk density of the soil the lower the CO2 emission. Thus, an increase in
the moisture content of the soil reduces carbon dioxide emissions.
Table 3 presents the significance of the observed correlation coefficients. Out of the total 10 correlations found between the
parameters, 1 was found to have been significant at a 5% level (r = -0.965) which is between total organic carbon (TOC) and
carbon emission (CE), this implies that an increase in total organic carbon lead to decrease in carbon emission, also in MC and
CE at r = -0.825 an increase in moisture content lead to decrease in carbon emission.
The result for total organic carbon (TOC) in forest locations is 1.7% and yam farm is 1.5% showing that those land uses are not
disturbed compared to cattle ranches and maize farms which TOC is 1.2% and 1.0%, therefore, there are clear difference in the
TOC storage from each land use as shown in Table 2
Table 2: Soil Parameters and CO
2
Emission
S/N
Locations
MC (%)
TOC (%)
CO
2
(g co
2
m
-2
d
-1
)
Soil pH
BD (kg/m
3
)
1
Maize farm
15.00
1.00
6.00
5.58
1.88
2
Cattle ranch
13.00
1.20
4.25
6.90
1.71
3
Yam farm
19.00
1.50
0.50
5.76
1.83
4
Forest
23.50
1.70
0.50
4.84
1.79
Table 3: Pearson Correlation between the soil parameters and Carbon emission (CE)
BD
MC
pH
TOC
CE
BD
1
0.199
-0.598
-0.193
0.128
MC
1
-0.860
0.895
-0.825
pH
1
-0.541
0.452
TOC
1
-0.965*
CE
1
Figure 6 shows that the higher the moisture content the lower the emission of carbon dioxide from the soil, with the relationship
R
2
= 0.681 which is high and it means moisture content affects CO
2
emission.
Figure 6: Graph showing the relationship between the moisture content and CO
2
emission
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 10
Figure 7: Grain size graph for Maize farm
Figure 8: Grain size graph for Yam farm
Figure 9: Grain size graph for Cattle ranch
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 11
Figure 10: Grain size graph for Forest
The above Figure 7 to 10-grain size analysis graph, indicates that the graph moves from higher elevation to lower elevation based
on their sieve sizes, the first three points upward are coarse soil, the second three grain sizes indicate sandy soil and the remaining
two points are silt soil. This depicts the percentage of each size of grain that was contained within a soil sample of the selected
locations which predicts the behavior of the soil in the locations.
IV. Conclusion
In the estimation of carbon dioxide emission on some agricultural land use, in which sodium hydroxide was used as a reagent for
the emission, during the experiment the soil parameter that affects the emission is soil moisture content, the highest carbon
emission was observed in maize farm which is 6g CO
2
m
-2
d
-1
. According to the results from each location (maize farm, yam
farm, cattle ranch and forest), shown that their rate of emitting carbon dioxide is different, the physical and chemical properties of
the soil also contributed to the emission in particular moisture content MC, because the higher the moisture content the lower the
emission of CO
2
, also total organic carbon TOC, the location that emitted higher rate of CO
2
which is maize farm has lowest
storage of TOC with a rate of 1.0%.
Also, results obtained explain further that the highest TOC storage was found in forest locations with a rate of 1.7% which
emitted the lowest carbon dioxide among the locations which is 0.5g CO
2
m
-2
d
-1
because the forest land is undisturbed, in the
field of the study each land use emits different rate of CO
2
except yam and forest location. therefore, deforestation, burning of
fossil fuel, land overgrazing and bush burning must be avoided then encourage afforestation and bush fallow. In terms of climate
change CO
2
emission has brought rapid disorder in weather patterns which leads to changes in the hydrological pattern that make
weather unpredictable which results in water scarcity and flooding of the environment.
References
1. Bellarby, J., Lorenzo, D. S. S., Emma, K. F., David, R. R., Paul, S., and Jon L. (2020): Quantifying soil carbon
sequestration in agricultural soils: A review. Soil Science Society of America Journal, 84(3), 531-545.
2. Deb, S., Bhadoria, P. B. S., Mandal, B., Rakshit A., and Singh H. B. (2015): Soil Organic Carbon: Towards Better Soil
Health, Productivity and Climate Change Mitigation. Climate Change and Environmental Sustainability, 3(1): 26 – 34.
3. Donovan, G. H., Brandly, J. S., John, R. P., Polly J. E., Stephen, M. O., Sarah, M. E., and Kristine, M. B. (2021): Carbon
sequestration in agricultural soils: A review of the evidence and a framework for decision-making. Environmental
Research Letters, 16(4), 044002.
4. FAO (2015): “Implications for Climate Change” Food Security with Climate Change, pp 1 – 6.
5. IPCC. (2020): Climate Change and Land. An IPCC special report on climate change, desertification, land degradation,
sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Cambridge University
Press.
6. IPCC. (2014): Climate Change 2014: Synthesis, Report Contribution of working GroupsI, II and III to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change. Geneva: IPCC.
7. Kane, D. (2015): Carbon Sequestration Potential on Agricultural Lands: A Review of Current Science and Available
Practices. Journal of Soil Organic Carbon dynamics. Pp 53 – 69.
8. Keestrea, S.D., Bouma, J., Wallinga, J., Tittonell, P., Smith, P., Cerda, A., Montanarella, L., Quinton, J. N., Pachepsky,
Y., Vander Putten, W. H., Bardgett, R.D., Moolenaar, s., Mol, G., Jansen, B. and Fresco, L. O. (2016): The Significance
of Soils and Soil Science Towards Realization of the United Nations Sustainable Development Goals, Soil. 2, 111- 128.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIII, Issue VII, July 2024
www.ijltemas.in Page 12
9. Martin, J. G. and Bolstad, P. V. (2005): Annual Soil Respiration in Broadleaf Forests of Northern Wisconsin. Influence
of Moisture and Site Biological, Chemical and Physical Characteristics. Biogeochemistry 73(1): 149- 182.
10. Ryan, M. G., and Law, B. E. (2005): Interpreting, Measuring and Modeling Soil Respiration. Biogeochemistry 73 (1): 3-
27.
11. Zavarzin, G. A., and Kudeyarov, V. N. (2006): Soil as the Key Source of Carbonic Acid and Reservoir of Organic
Carbon on the Territory of Russia. Herald of the Russian Academy of Sciences, 76 (1): 12- 26.
12. Zeman, F. S. and Lackner, K. S. (2004): Capturing Carbon dioxide directly from the atmosphere. World Resources, 16:
62- 68.
