Article citation information:
Salisu, U.O.,
Fasina, S.O., Shodunke, H.T., Akanmu, A.A., Sanni, S.M., Olorunfemi, S.O. Influence
of transport operations on the changing local climate in Nigeria’s
southwestern cities. Scientific
Journal of Silesian University of Technology. Series Transport. 2023, 121, 203-222. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2023.121.13.
Umar Obafemi SALISU[1],
Simeon Oluwagbenga FASINA[2],
Hazzan Tunde SHODUNKE[3],
Ayobami Ademola AKANMU[4],
Sekinat Motunrayo SANNI[5],
Samuel Oluwaseyi OLORUNFEMI[6]
INFLUENCE OF TRANSPORT OPERATIONS ON THE CHANGING LOCAL CLIMATE IN
NIGERIA’S SOUTHWESTERN CITIES
Summary. The
activities of transport operations exhibit both positive and negative outcomes.
Its negative effects on human health and the sustainability of the environment
are of interest in this study. As a result, the study investigated the
influence of transport operations on the changing local climate in Nigeria's
southwestern cities. It investigated motorists' socioeconomic status (SES) and
travel characteristics; the salient components of transport operations
contributing to greenhouse gas emissions (GHG emissions); the effect of GHG
emissions from transport operations on the local climate; transport
externalities contributing to local temperature changes; and the effect of GHG
emissions from transport operations on human health in the research location.
This study employed a cross-sectional research design, utilizing systematic
sampling to collect 580 copies of questionnaires administered to commercial
motorists found in queues across two randomly selected parks in each capital
city within the region. Both descriptive and inferential statistics (ANOVA and
Linear Regression) were used to analyze the data. The study found that 60% of
the motorists were middle-aged (aged between 36 and 45). The majority (70%)
drive an average of 100 to 150 km, and premium motor spirit (PMS) is the
primary source of energy for 95% of them. The nature and condition of the fuel
in use are the top-ranked components of transport operations contributing to
GHG emissions. The result of the ANOVA revealed a significant variation among
the components of transport operations contributing to GHG emissions (F =
28.302, p = 0.000<0.05). Meanwhile, the linear regression results indicate
that vehicular GHG emissions have a significant impact on the local climate
(F1⁄578=30.091, p=0.000<0.05). Traffic congestion and bad road
conditions were the top-ranked transport externalities contributing to the
changing local climate. The most common effects of GHG emissions on human
health were headaches and difficulty breathing. Considering these findings, this
study suggests the best tactics to lessen the effects of GHG emissions from
transport operations, which adversely affect the local climate and human health
in the study area.
Keywords: cities,
climate change, greenhouse gas GHG emissions, transport, transport
externalities
1.
INTRODUCTION
Transport is as old as the existence of man. It is
inextricably linked to man's historical development, as accessibility and
mobility are unquestionably necessary for achieving and satisfying human needs
[18, 21]. Transport is a modern civilization's facilitator; it is a catalyst
through which any society develops with the desired momentum, and it has played
extensive and pivotal roles in the transformation of any economy over time [2].
Salisu [21] opined that the demand for transport, which is a function of human
survival and societal interaction, will no doubt remain an increasing and
continuous one so long as the earth continues to rotate in its elliptical
orbit. Hence, there is no escape from it, as people and goods must move and
basic human needs must be sought for; “it is a demand of all
demands" [4, 9]. There is no question that the availability, practicality,
functionality, dependability, safety, and quality of transport modes are
essential to human existence and survival, as well as the sustainability of
their surroundings. As a result, it is imperative that communities maintain an
effective transport system that will support their social, economic, and
environmental sustainability, especially in cities [2, 3, 17].
The
contributing effects of transport on economic growth and development are both
positive and negative. Studies on the positive effects of transport systems on
economic development both in developed and developing nations have been well
discussed and established in the literature [1, 2-4, 7, 9, 11, 17, 20]. Of
interest to this study is the impact of transport on the changing local climate
due to the operational nature of the available transport system. Transport
operations, particularly the popular land-based mode, which is commonly used
for both non-discretionary and discretionary urban travel, are characterized by
noticeable costs, which include but are not limited to increasing levels of
motorization and car ownership, environmental damage, deteriorating air
quality, crime activities, and urban stress [17, 20]. The consequential effect
of the costs, especially the increasing growth of car ownership and
motorization levels, undermines the capacity of transport infrastructure and
the overall performance of transport systems as car ownership rates are rapidly
increasing in developing countries, including Nigeria. Meanwhile, the growing
use of automobiles, particularly in Nigerian cities, is accompanied by the
government's gradual withdrawal from providing an efficient public transport
system, as well as substandard transport infrastructure facilities, a poor
administrative and institutional framework for public transport operations,
poor network capacity orientation and safety, inadequate public mobility options
and operational situations, and poor conditions of public vehicles, leading to
basic challenges that cannot be easily managed, such as terrible traffic
congestion, environmental degradation, air and water pollution, urban sprawl,
and stress.
Accordingly,
Gilbert [7] observed that the increasing demands for mobility options along
with the attributed challenges of transport operations in cities are the
drawback effects of inadequate transport infrastructural provision and
development, which consequently affect the social and economic development of
cities and the sustainability of the environment. One of the obvious
consequences of transport operations that obviously influence the environment
is the greenhouse gas emissions (GHG emissions) from the transport facilities,
which are becoming unavoidable in most countries, particularly in emerging
nations such as Nigeria, where transport externalities are still very high and
alarming. The persistent emission of greenhouse gases (GHGs), which include
nitrous oxide, carbon dioxide, ozone, methane, and halocarbons, mainly causes
global warming and climate change [13]. The climate continues to change because
of global warming, with noticeable effects including altered rainfall patterns,
rising sea levels, melting ice and snow, and an increase in the frequency and
severity of extreme weather events and temperatures [10]. Undoubtedly, GHG
emissions from the transport system are the principal causes of the warming of
the planet and the changing climate [8, 23]. Sperling and Cannon [23] opined
that the transport sector is a major source of GHG emissions as it contributes
about one-fourth of global GHG emissions, causing climate change, and the
United States takes the lead amongst all other countries in the world in terms
of transport-related GHG emissions. According to Chapman [5], transport-related
externalities degrade air, water, and soil through vehicular exhaust, hazardous
material spillage, soil, and noise pollution from vehicle operations, causing
hearing problems and soil contamination, and igniting accident occurrences that
result in fatalities or a risk to the lives of passengers and property [6].
Hence, Chapman [5] observed that the overreliance on land transport and
increasing consumption and exhaustion of fossil fuels appear to be responsible
for the climate's long-term damage across the globe. Nigeria is not exempt from the latter.
Furthermore, Salisu [21] stated that Nigerian cities
are seeing a high pace of urbanization, urban expansion, and population growth,
together with a rise in the demand for physical mobility and increasing car
ownership, without adequate transport institutional framework and
administrative capacity to manage the challenges posed by this unprecedented
population increase and urbaninsation rate. The consequential effects of
unprecedented population increase, unguided urbanization, increasing physical
travel demand, and poor transport operations not only pose a serious threat to
human health and the sustainability of cities but also exacerbate local climate
and degrade environmental resources such as air pollution and heat islands.
While unethical and poor transport operational situations, increasing physical
travel demand, and human activity primarily through transport, as well as the
weak transport institutional framework and administrative capacity, have
recently posed a significant threat to climate and environmental
sustainability, resulting in environmental stress, increasing the average
temperature of the surrounding areas, and further contributing to climate
challenges, especially global warming. Regrettably, the accumulation of
greenhouse gases in the atmosphere brought on by increasing vehicle combustion
and related transport activities is what is responsible for the climatic problems.
Several efforts to address climate issues, however, have been of global concern
to stakeholders in the transport and environmental management industries,
particularly professionals, the government, non-governmental organizations, and
others.
Unfortunately, advocacy through empirical studies and
measures to address the impact of transport on local climate change in Nigeria
is still very low or lagging. Therefore, establishing the influence of
transport on the changing local climate and human health, as well as
identifying measures to mitigate the negative consequences caused by transport
operations in Nigeria's cities, became pertinent and thus formed the focus of
this study. Undoubtedly, several studies in the global south have shown much
effort (empirical and theoretical) on adaptation of transport infrastructure to
the changing climate, mitigation of transport operational risk factors, and
strategies for reducing emissions of GHGs, congestion, and crashes through
governmental and non-governmental reports and research articles. There is,
however, a paucity of empirical investigation into the effect of transport on
local climate change in the global north, especially in Nigeria. It is against
this backdrop that the study examined the influence of transport on the
changing local climate in Nigeria's southwestern cities. To
achieve this aim, the following objectives guided the study: examined
motorists' socioeconomic status (SES) and travel characteristics; examined
motorists' perceptions of the salient components of transport operations
contributing to greenhouse gas emissions (GHG emissions); assessed the effect
of GHG emissions from transport operations on local temperature or climate;
examined the transport externalities contributing to local temperature changes;
examined the effect of GHG emissions from transport operations on human health;
and examined the measures to reduce GHG emissions from transport operations
towards mitigating its devastating effects on our immediate environment and
human health. Filling this research gap will advance our understanding of
transport and climate change.
2. LITERATURE REVIEW
The
intricate relationship between transport operations and the changing local
climate in Nigeria's southwestern cities has become a focal point for
researchers, given its profound socioeconomic and environmental implications.
This literature review, drawing insights from authoritative sources such as
ActionAid [24], McCollum and Christopher [12], Nirjar, Jain, and Parida [14],
and Ribeiro et al., [19], aims to elucidate the multifaceted impact of
transport operations on climate change, encompassing economic, social, and
environmental costs, as well as greenhouse gas (GHG) emission reduction,
mitigation measures, and climate change adaptation.
Economic,
Social, Environmental Impacts of Climate Change:
ActionAid
(2006), referenced in [24], sheds light on the economic ramifications of supply
and demand fluctuations induced by climate change. Frequent climate-related
disasters, like floods, contribute to soil erosion, infrastructure damage, and
reduced agricultural output, resulting in food shortages and increased costs
for relief, rehabilitation, and pollution management. References [12, 24]
underscore the pivotal role consumer behaviour plays in influencing the
sustainability of businesses, which is undermined by the effect of climate
actions, extending its influence on critical domains such as water
availability, ecosystem services, energy supply, and various industries
globally. In specific scenarios, climate change can lead to severe
environmental consequences, including ecosystem degradation, community
devastation, asset loss, disruption of local economies, and mass migrations
[10, 24]. Ribeiro et al. [19] highlight that the actions of transport systems
significantly contribute to climate change, accounting for 20-25% of global
energy consumption and carbon dioxide emissions. Odjugo (2009) cited in
reference [15] noted that beyond transport factors, general human factors such
as industrialization, technological development, urbanization, deforestation,
fossil fuel combustion, etc., and natural factors including solar radiation
quality and quantity, the astronomical position of the earth, etc. are
significant causes of climate change. The adoption of comprehensive urban
planning and the coherent complete street transport model emerge as promising
approaches for sustainable urban development, aiming to mitigate GHG emissions,
environmental degradation, and social impacts associated with transport-related
activities [10, 22].
GHG Emission
Reduction, Mitigation Measures, and Climate Change Adaptation:
Studies,
such as McCollum and Christopher [12], underscore the role of urban planning in
mitigating GHG emissions. Densely populated areas with diverse land uses tend
to emit fewer GHG emissions from travel, emphasizing the importance of
comprehensive urban planning in reducing environmental impact. Climate
challenges persist, with transport-related GHG reductions often deemed more
expensive in cities due to factors like low fuel price elasticity, high demand
for personal travel, and difficulties in adopting new technologies. Mitigating
GHG emissions necessitates strategic interventions, including low-carbon fuels,
vehicle efficiency improvements, and travel reduction based on a complete
street model [24]. Enhancing vehicle efficiency through incremental vehicle
technologies, advanced smart technologies, and improved on-road operating
procedures is proposed to achieve comprehensive and rapid reductions [12, 24].
Furthermore,
a summary of the literature reviewed highlights the inadequacies of developing
countries in planning and implementing resilient and adaptive measures to
address global climate change. Adaptation efforts such as the use of
infrastructure resilience and community-based resilience methods are adjustment
strategies capable of addressing the changing precipitation pattern, potential
climate change effects, and the vulnerability of people and natural systems
[15]. Designing and constructing transport infrastructure (buildings, roads,
and bridges) to withstand extreme weather events and changing climate
conditions, implementing measures such as elevated structures, flood barriers,
and improved drainage systems to reduce vulnerability, and providing
climate-smart agricultural practices, early warning systems, and
capacity-building initiatives are major adaptation measures to address climate
change [15].
Literature
Gap:
Despite
the comprehensive insights provided by the existing literature, significant
research gaps persist. In-depth studies are needed to explore the nuanced
relationship between transport operations and local climate change, utilizing a
mixed-methodology approach—specifically, a “survey and
observational methodology.” This approach will capture subjective
insights from motorists through questionnaire responses, allowing a deeper
understanding of their travel behaviours, perspectives on specific components
of transport operations contributing to GHG emissions, transport externalities influencing
local climate changes, and the health impacts of GHG emissions from transport
operations. Concurrently, objective data collection from direct sampling of
vehicle parameters is essential to scrutinize the direct effects of GHG
emissions on local temperature changes. This research aims to provide a
comprehensive understanding of the impact of transport operations on local
climate change, which is essential for informed policymaking and sustainable
development amidst evolving climate challenges in Nigerian cities.
3.
STUDY AREA AND METHODOLOGY
3.1.
Study area
Nigeria's southwestern
region consists of the six capital cities and states, including Ikeja-Lagos,
Abeokuta-Ogun, Ibadan-Oyo, Osogbo-Osun, Akure-Ondo, and the Ado-Ekiti-Ekiti
States (Fig. 1). The Southwestern region, which is one of the most prominent
geopolitical zones in Nigeria, lies between latitudes 6oN and 81/2oN
of the equator and longitudes 3oE and 5oE of Greenwich
Meridian Time (GMT), with a total area of 79, 048 sq. kilometres (Fig. 1 and
Fig. 2). Specifically, several treaties struck with the local population
allowed for the region's inclusion into the British Empire during the final
decade of the nineteenth century. The purpose of the incorporation was to give
the British complete authority over the region's material and human resources,
so they could build significant physical infrastructure. This includes the
contemporary transport infrastructure that has taken on the role of the area's
original, pre-colonial transport systems. The region is full of transport
terminals, networks, and operations, most especially the railroad and maritime
transport that began in the area [16]. However, the region is the Nigerian
transport hub, with freeways linking it with other areas of the country; one
international airport in Lagos; and domestic airports in Ibadan and Akure,
aside from seaports in Lagos and inland waterways in the coastal parts of the
region [2].
Notable expressways in the region include the
Lagos-Ibadan highway, the Ibadan-Ife-Ilesa highway, the Lagos-Ore-Benin
expressway, the Ibadan-Oyo-Ilorin expressway, the Lagos-Abeokuta highway, and
the Apapa-Osodi expressway, among others. Importantly, the Lagos-Ibadan and
Lagos-Abeokuta highways act as interstate highways leading to Oyo State and
Ogun State, respectively, and are the main thoroughfares connecting the
nation's largest cities. Furthermore, the region has the headquarters of the
Nigerian Railway Corporation (NRC), which is in Lagos, and a series of
pipelines carrying fluids, gases, and petroleum firms in, within, and outside
the cities in the region. Moreover, the Southwestern region is blessed with
water bodies that allow for inland water transport operations and maritime or
sea shipping businesses, as well as being characterized by both international
and domestic airports for inter-city passenger and freight flight services.
3.2. Methodology
This study used a mixed-method
research methodology consisting of a cross-sectional survey and an
observational method. The combination of this mixed methodology allows for both
subjective insights from drivers through the questionnaire responses and
objective data collection from the direct observation of vehicle and local
climate parameters. The cross-sectional survey was adopted to capture
subjective insights from motorists through questionnaire responses, allowing a
deeper understanding of their travel behaviours, perspectives on specific
components of transport operations contributing to GHG emissions, transport
externalities influencing local climate changes, and the health impacts of GHG
emissions from transport operations. Concurrently, objective data collection
from direct sampling of vehicle and local climate parameters was essential to
determine the direct effects of GHG emissions on local temperature changes. However, the nature of the research objectives, the interaction of
relevant variables in the research, as well as evidence from the literature
reviewed, influenced the choice of a mixed-method research methodology. Both
primary and secondary data formed the sources of data used in this study. The
primary data employed was a questionnaire survey complemented with field
observation involving the use of vehicular emission and local temperature test
apparatus. The questionnaire survey was administered to commercial motorists at
major parks in the selected cities. The thermometer was used to pick the local
temperature, while the emission test apparatus, the "carbon meter,”
helped to determine the rate of carbon emissions from the sampled vehicles. The
secondary data was sourced from both published and unpublished materials,
including journal articles, reports, and textbooks.
Fig. 1.
Nigerian map displaying the Southwestern geopolitical zone (research region)
Fig. 2. Map
of the Southwestern region
Furthermore, this study
adopted a multistage sampling technique comprising random, quota/proportionate,
and systematic sampling methods. In the first stage, a random sampling
technique was employed to select two major motor parks in each capital city,
including Abeokuta, Ado-Ekiti, Akure, Ibadan, Ikeja, and Osogbo. Due to the
lack of accurate information on the number of registered commercial motorists
with personal vehicles across the selected capital cities, the second stage
involved assigning a proportional sample size of fifty (50) to allocate numbers
to samples (commercial motorists in their vehicles) in a systematic approach
after the selection of the first vehicle and its driver in the queue. In the
third stage, a systematic sampling technique was used to select one out of
three motorists in their respective vehicles from the queues at the randomly
selected motor parks in each capital city based on the allotted numbers. In
other words, a total of 600 copies of a questionnaire were administered across
the study area, of which 580 copies were completed, representing a 97% response
rate (see Table 1). The questionnaire design included both closed-ended and
open-ended questions. The Likert scale was majorly considered for the
closed-ended questions, while the questions were structured based on the
research objectives. Simultaneously, immediately after the completion of the
questionnaire administration, emission rates were collected from the 600
vehicles along with local temperature data around the sampled vehicles.
Worthwhile, the gathered data underwent presentation and analysis
employing a combination of descriptive and inferential statistical methods.
Descriptive statistics utilized frequency and percentage tables along with the
Relative Mean Index (RMI). Meanwhile, inferential techniques, including linear
regression analysis and Analysis of Variance (ANOVA), were employed to achieve
the hypothesized propositions. Linear regression assessed the impact of vehicle
emission rates on the fluctuating climate, specifically measured by local
temperature. ANOVA was used to determine the statistical variation between the
perceived salient factors of transport operations influencing GHG emissions in
the selected cities. In other words, the Relative Mean Index (RMI) used for
presentation and analysis relies on data collected through Likert’s scale
using a four-point grading system of Strongly Agree, Agree, Disagree, and
Strongly Disagree. The process of estimating the RMI is presented as follows:
i.
Each evaluation was given a weighted value of 4, 3, 2, and 1,
correspondingly, indicating strong agreement, agreement, disagreement, and
strong disagreement.
ii.
The addition of the product of the response for each variable rating
and its corresponding weight value was used to calculate the weighted value of
SWV as a sum. Thus, the mathematical expression is:
SWV =
Where:
SWV = Summation of
Weight Value,
Y
The Mean Index
Value [MIV] is calculated by dividing the sum of RIM by the number of variables
studied, whereas the Relative Mean Index [RMI] for each variable was determined
by dividing the SWV by the total number of replies. Unless stated otherwise, a
higher RMI corresponds to a better level of efficacy for the variable being
examined. This can be stated quantitatively as:
RMI =
In other words, to
run the inferential statistics analysis, the collected data was transformed
into a dichotomous form of binary digits 0 and 1 and presented as
"Strongly Agree" or "Agree" =1 and "Strongly
Disagree" =0. This transformed data of the indicators of transport
externalities (independent variables) was regressed with the local temperature
rate (dependent variable) as well as used to transform the salient factors of
the transport operation contributing to GHG emissions into dichotomous form and
used for the test of the postulated hypotheses. However, version 21 of the
Statistical Package for Social Sciences (SPSS) software was used to do both the
data presentation and analysis.
Tab.
1
Sample
Size and Response Rate of the Respondents (Motorists)
|
Southwest capital cities |
Proportional sample size |
Response rate |
|
Abeokuta |
100 |
100 |
|
Ado-Ekiti |
100 |
94 |
|
Akure |
100 |
96 |
|
Ibadan |
100 |
100 |
|
Ikeja |
100 |
100 |
|
Osogbo |
100 |
90 |
|
|
600 |
580 equivalent of 97% |
4. RESULTS AND
DISCUSSION
4.1. Motorists’
Socioeconomic Status (SES) and Travel Characteristics
The results of the data
gathered and analyzed on the socioeconomic status of the respondents
"motorists" are presented in Table 2. The findings revealed that the
respondents were mostly male (96%), while 4% of the respondents were female.
The vast majority (60%) are between the ages of 36 and 45; they are a
middle-aged and active economic group. In addition, over three-quarters (75%)
are married, 90% have a formal education, and the remaining 10% have no formal
education. It's worth noting that the vast majority, 75%, are owners of the
vehicles used for commercial transport services. The majority (80%) earned
between $100,000 and $150,000 monthly from the transport business, while 90% of
the respondents indicated that they were full-time commercial drivers.
Worthwhile, 60% have between 4 and 6 people living in their household, and a
majority of 70% have more than one wife. In other words, most (70%) run
intra-city transport services and cover an average of 150 kilometers of trips
per day (70%). Significantly, 95% of the respondents use Premium Motor Sprit
(PMS) as a type of fuel for commercial transport services, which indicates the
dominance of the use of PMS in the study area and obviously may contribute to
the GHG vehicular emissions. The majority (80%) of the motorists operating
during peak hours consumed over 40 liters of PMS depending on the daily traffic
situation. In the categories of vehicles owned and used for commercial
services, the majority (70%) of indicted Toyota products include the Liteace,
Sienna, Coaster, and Picnic. Findings also revealed that most (75%) of the
vehicles owned are secondhand (Tokunbo), meaning the respondents are not the
first users. Meanwhile, 70% of the respondents revealed that their vehicles
have spent over 5 years with them. Regarding the frequency of maintenance, the
majority (70%) indicated they engaged in monthly scheduled service maintenance
due to the kilometers traveled.
Tab. 2
Motorists’ Socioeconomic Status (SES) and Travel Characteristics
|
Gender Structure |
Age Classification |
||||
|
Nature |
Frequency |
Percentage |
Range |
Frequency |
Percentage |
|
Female |
23 |
4.0 |
18-25 |
52 |
9.0 |
|
Male |
557 |
96.0 |
26-35 |
87 |
15.0 |
|
Total |
580 |
100.0 |
36-45 |
348 |
60.0 |
|
Marital Status |
46-60 |
93 |
16.0 |
||
|
Status |
Frequency |
Percentage |
Total |
580 |
100.0 |
|
Single |
87 |
15.0 |
Educational Attainment |
||
|
Married |
435 |
75.0 |
Level |
Frequency |
Percentage |
|
Others |
58 |
10.0 |
No formal education |
58 |
10.0 |
|
Total |
580 |
100.0 |
Primary |
87 |
15.0 |
|
Occupational Status |
Secondary |
377 |
65.0 |
||
|
Nature |
Frequency |
Percentage |
Tertiary |
58 |
10.0 |
|
Full-time motorist |
522 |
90.0 |
Total |
580 |
100.0 |
|
Part-time motorist |
58 |
10.0 |
Average Monthly Income |
||
|
Total |
580 |
100.0 |
Range |
Frequency |
Percentage |
|
Ownership of the Vehicle |
Below #50,000 |
29 |
5.0 |
||
|
Ownership |
Frequency |
Percentage
|
#50,000-#100,000 |
58 |
10.0 |
|
Yes, I am
the owner |
435 |
75.0 |
#100,001-#150,000 |
464 |
80.0 |
|
No, I
operate on hire services |
145 |
25.0 |
#150,001-#200,000 |
29 |
5.0 |
|
Total |
580 |
100.0 |
Total |
580 |
100.0 |
|
Nature of
Transport Services Rendered |
Household Size |
||||
|
Number |
Frequency |
Percentage |
Number |
Frequency |
Percentage |
|
Intra-city |
406 |
70.0 |
1-3 |
174 |
30.0 |
|
Inter-city |
174 |
30.0 |
4-6 |
348 |
60.0 |
|
Total |
580 |
100.0 |
Above 6 |
58 |
10.0 |
|
Daily Travel Distance |
Total |
580 |
100.0 |
||
|
Length |
Frequency |
Percentage |
Number of Spouse |
||
|
Less than 100km |
116 |
20.0 |
Number |
Frequency |
Percentage |
|
100 to 150 km |
406 |
70.0 |
One wife |
174 |
30.0 |
|
Above 150km |
58 |
10.0 |
More than one wife |
406 |
70.0 |
|
Total |
580 |
100.0 |
Total |
580 |
100.0 |
|
Rate of
Daily Energy Used |
Type of
Fuel/Energy Used |
||||
|
Volume |
Frequency |
Percentage |
Type |
Frequency |
Percentage |
|
Less
than 20 liters |
29 |
5.0 |
PMS |
551 |
95.0 |
|
20 to 40 litters |
87 |
15.0 |
Diesel |
29 |
5.0 |
|
Above 40 liters |
464 |
80.0 |
Electricity/Solar |
0 |
0.0 |
|
Total |
580 |
100.0 |
Total |
580 |
100.0 |
|
Brand of
Vehicle Used for Transport Services |
Category of
Vehicle Used for Transport Services |
||||
|
Brand |
Frequency |
Percentage |
Category |
Frequency |
Percentage |
|
Toyota products |
406 |
70.0 |
Brand-New |
29 |
5.0 |
|
Nissan products |
70 |
12.0 |
Secondhand (Tokunbo) |
435 |
75.0 |
|
Mazda products |
58 |
10.0 |
Third User (Nigeria) |
116 |
20.0 |
|
Mercedes products |
29 |
5.0 |
Total |
580 |
100.0 |
|
Others products |
17 |
3.0 |
Frequency
of Vehicle Maintenance |
||
|
Total |
580 |
100.0 |
Period |
Frequency |
Percentage |
|
Age of Vehicle |
Weekly |
29 |
5.0 |
||
|
Age |
Frequency |
Percentage |
Monthly |
406 |
70.0 |
|
Less than 5 years |
174 |
30.0 |
Quarterly |
116 |
20.0 |
|
Above 5 years |
406 |
70.0 |
Twice a year |
29 |
5.0 |
|
Total |
580 |
100.0 |
Total |
580 |
100.0 |
4.2. Salient Components of Transport Operations
Contributing to GHG Emissions
Table 3 reveals the results of the analysis on
motorist perceptions of the salient components of transport operations that
contribute to the GHG emissions and changing local climate across the study
area, using the Relative Mean Index (RMI) and Mean Index Value (MIV). Findings
revealed that the vehicular energy type, or source of energy, is the
predominant component contributing to greenhouse gas emissions (3.9347). This
finding is corroborated by the fact that the majority of respondents (95.0%)
rely on premium motor spirit (PMS) over other energy sources for commuting
services in the study area. The factors that placed second, third, fourth, and
fifth, in order of precedence, were journey time (3.6134), vehicle engine
condition (3.5206), road condition (3.5223), and travel distance (3.3789). In
the research area, vehicle condition was shown to be the least significant
contributor to greenhouse gas emissions. Considering this, the findings showed
that 50% (5 out of 10) of the transport system's source variables scored higher
than the MIV of 2.9387.
Tab. 3
Salient Components
of Transport Operations Contributing to GHG Emissions
|
Transport
Sources of Greenhouse Gases Emission |
SD |
D |
N |
A |
SA |
TWV |
RIM |
MIV |
RK |
|
Vehicle engine condition |
21 |
80 |
408 |
1540 |
0 |
2049 |
3.5206 |
2.9387 |
4 |
|
Nature and condition of engine oil for vehicle servicing |
258 |
298 |
207 |
380 |
55 |
1198 |
2.0584 |
9 |
|
|
Traffic control devices and officers |
344 |
180 |
33 |
104 |
555 |
1216 |
2.0893 |
8 |
|
|
Vehicle condition |
273 |
340 |
237 |
240 |
0 |
1090 |
1.8729 |
10 |
|
|
Nature and consumption of energy/fuel in use |
67 |
0 |
0 |
1944 |
145 |
2290 |
3.9347 |
1 |
|
|
Vehicular fuel system |
186 |
232 |
267 |
652 |
140 |
2049 |
2.5378 |
7 |
|
|
Nature of road condition |
135 |
28 |
843 |
408 |
250 |
1198 |
3.5223 |
3 |
|
|
Vehicular engine size/capacity |
61 |
242 |
162 |
368 |
1270 |
1216 |
2.8591 |
6 |
|
|
Travel time |
135 |
290 |
612 |
236 |
195 |
1090 |
3.6134 |
2 |
|
|
Total distance travelled |
18 |
292 |
357 |
784 |
515 |
2290 |
3.3789 |
|
5 |
4.2.1. Hypothesis testing
Hypothesis One (H0:
There is no statistical variation among the salient components of transport
operations contributing to GHG emissions)
Further investigation was conducted using
ANOVA to determine whether there is a statistical variation among the salient
components of transport operations contributing to GHG emissions. The result of
the ANOVA shows that there is a statistically significant variation among the
salient components of transport operations that contribute to GHG emissions in
the study area.
|
Tab. 4 Tests of Between-Subjects Effects (where or
not there is a statistical variation among the salient components of
transport operations contributing to GHG emissions) |
||||||
|
Source |
Type III Sum of Squares |
Df |
Mean Square |
F |
Sig. |
|
|
1 |
Intercept |
15.255 |
I |
.401 |
30.091 |
.000 |
|
Error |
16.343 |
579 |
.013 |
|
|
|
|
Total |
31.599 |
580 |
|
|
|
|
4.3. The Effect of the Vehicular Greenhouse Gas
Emissions on Local Temperature or Climate
Table 5 presents the result of the vehicle's GHG emissions on the local
temperature or climate. Descriptively, the results presented in Table 5 show
that 15.0% of the respondents run emission tests on their vehicles annually,
5.0% run emission tests on their vehicles once in the last 5 years, and 80.0%
of the respondents have never conducted or run emission tests on their
vehicles. By implication, the majority (80.0%) of motorists are carefree about the
emission status of their vehicle and thus not worried about the extent to which
their vehicle operation affects or pollutes the local climate.
Tab. 5
Frequency of theVehicle Emission Test
|
Frequency of emission test |
Frequency |
Percentage |
|
Annually |
29 |
15.0 |
|
Once in the
last 5 years |
87 |
5.0 |
|
Never run emission test |
464 |
80.0 |
|
Total |
580 |
100.0 |
4.3.1 Hypothesis
Two (H0: Vehicular GHG
emissions does not statistically influence local
temperature or climate)
Further investigation
was conducted in order to better understand the statistical effect of vehicle
GHG emissions on local temperatures or climate. A vehicle emission test was
conducted on 580 vehicles and their local temperature was picked simultaneously.
The independent variable “the vehicle GHG emission (g)” was
achieved through the vehicle emission test conducted on the vehicles, which was
done using the carbon meter to track the carbon emitted by a vehicle, which is
equivalent to the measure of greenhouse gas. While the dependent variable
“changing local climate” was measured by the temperature of the
vehicles sampled across the study area, the analysis was conducted using linear
regression, and the result is presented in Table 6. The outcomes depicted in
Table 6 display the "R" value, serving as the linear regression
correlation coefficient, gauging the accuracy of predicting the dependent
variable "local temperature change." With a value of 0.795, it
indicates a commendable level of prediction. The R square (R2) value, denoting
the coefficient of determination, stands at 0.685, implying that 68.5% of the
variability in the dependent variable (local temperature or climate) can be
elucidated by the independent variables. Simultaneously, the adjusted R square
(Adj. R2) is 0.667, signifying that the model's accuracy of prediction accounts
for 67%.
Examining the F-Ratio
in the ANOVA, which assesses the overall significance of the regression model's
fit for the regressed data in Table 4.8, the findings disclose F
Tab. 6
Model summary of the linear regression
(effect of
vehicle GHG emissions on the local temperature or climate)
|
Model Summary |
||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
1 |
.795a |
.683 |
.667 |
.11550 |
|
ANOVAa |
||||||
|
Model |
Sum of Squares |
Df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
15.255 |
1 |
.401 |
30.091 |
.000b |
|
Residual |
16.343 |
578 |
.013 |
|
|
|
|
Total |
31.599 |
579 |
|
|
|
|
4.4. Transport
Externalities Contributing to Changing Local Climate/ GHG Emissions
Significantly, transport operations are accompanied by several
externalities that contribute to the changing local climate and GHG emissions.
In a bid to comprehend the impact of transport externalities on greenhouse gas
(GHG) emissions in the research area, Table 7 elucidates the specific external
factors associated with global warming and GHG emissions. It is notable that
respondents assessed twelve identified transport externalities, and the
resulting analysis is presented. Notably, the analysis disclosed that 75% (9
out of 12) of the transport externalities scored above the Mean Importance
Value (MIV) of 2.926. Traffic congestion (3.5670), poor road conditions
(3.4038), suboptimal energy/fuel and engine oil conditions (3.3213), inadequate
vehicle maintenance (3.2285), unregulated logistics functions (3.2268), and
insufficient road capacity (3.2285) emerged as the predominant contributors to
greenhouse gas emissions in the research area. In other words, the weak
institutional framework and performance of the transport administrators ranked
the least.
Tab.
7
Transportation
Externalities Contributing to Changing Local Climate/ GHG Emissions
|
Externalities |
N |
R |
S |
A |
TWV |
RIM |
MIV |
RK |
|
Unguided logistics
functions |
4 |
208 |
690 |
976 |
1878 |
3.2268 |
2.9465 |
6 |
|
Over-dependency on
automobile usage |
27 |
920 |
189 |
128 |
1264 |
2.1718 |
12 |
|
|
Poor condition of
energy/fuel and engine oil in use |
11 |
168 |
582 |
1172 |
1933 |
3.3213 |
3 |
|
|
Traffic congestion |
0 |
118 |
402 |
1556 |
2076 |
3.5670 |
1 |
|
|
Weak institutional
framework for transport management |
43 |
186 |
171 |
15 |
1956 |
2.2608 |
11 |
|
|
Poor condition of
the vehicle in use |
14 |
266 |
423 |
1176 |
1879 |
3.2285 |
4 |
|
|
Weak traffic and
transport policy implementation |
187 |
156 |
0 |
1276 |
1617 |
2.7784 |
8 |
|
|
Bad road situation |
18 |
128 |
495 |
1340 |
1981 |
3.4038 |
2 |
|
|
Absence of
non-motorized transport facilities |
17 |
742 |
135 |
596 |
1490 |
2.5601 |
10 |
|
|
Unguided traffic
operation and trip distance |
4 |
208 |
690 |
976 |
1878 |
3.2268 |
|
4 |
|
Poor road capacity |
14 |
266 |
423 |
1176 |
1879 |
3.2285 |
|
6 |
|
Excesses by traffic
officers and poor traffic control devices |
187 |
156 |
0 |
1276 |
1617 |
2.7784 |
|
8 |
4.5. Effect of GHG Emissions from
Transport Operations on Human Health
It is worth knowing that the externalities
from transport operations, particularly the GHG emissions, have been found to
have a negative impact on human and public health. The concern in this study is
the effect of GHG emissions from transport operations on human health. Table 8
presents various health-related issues that are perceived to be caused by GHG
emissions, such as headaches, body aches, difficulty breathing, asthmatic
attacks, heavy eyes, a runny nose, difficulty sleeping at night due to underlying
health conditions, and other internal medical diseases or health problems such
as congestive heart failure, anxiety, etc. Findings revealed that a majority of
over 60% (5 of 8) of the health issues ranked above the Mean Index Value (MIV)
of 3.3926. This indicates that five (5), including headache (3.7629),
difficulty breathing (3.6426), body ache (3.6065), asthmatic attack (3.4605),
and heavy eyes (3.4605), which ranked first, second, third, and fourth,
respectively, are the most experienced health problems impacted by GHG
emissions from transport operations. In other words, GHG emissions had the
least impact on running noses and other internal medical diseases.
Tab. 8
Effect of GHG Emissions from Transport
Operations on Human Health
|
Nature of consequences |
SD |
D |
A |
SA |
TWV |
RIM |
MIV |
RK |
|
Headache |
14 |
38 |
174 |
1964 |
2190 |
3.7629 |
3.3926 |
1 |
|
Body ache/ tiredness |
35 |
76 |
144 |
1844 |
2099 |
3.6065 |
3 |
|
|
Asthmatic attack |
34 |
80 |
396 |
1504 |
2014 |
3.4605 |
4 |
|
|
Difficulty breathing |
12 |
16 |
468 |
1624 |
2120 |
3.6426 |
2 |
|
|
Heavy Eyes |
34 |
80 |
396 |
1504 |
2014 |
3.4605 |
4 |
|
|
Runny nose |
36 |
174 |
807 |
760 |
1595 |
2.7405 |
7 |
|
|
Difficulty sleeping at night due to an
underlying health condition |
24 |
324 |
309 |
1172 |
1829 |
3.1426 |
|
6 |
|
Other internal medical problems such as
congestive heart failure, anxiety, etc. |
36 |
174 |
807 |
760 |
1595 |
2.7405 |
|
7 |
4.5.1. Frequency of Medical Treatment due to Exposure
to GHG Emissions and Percentage of Income Spent on Medical Treatment
Respondents’ views on the frequency of
medical checkups and treatment at medical facilities due to exposure to GHG
emissions from transport operations were also sought in this study. Table 9
reveals the varied periods as indicated by respondents based on their
involvement in transport operations, particularly the hours spent while
driving. The majority (52%) of the respondents indicate that it is difficult to
estimate the frequency, hence opting for it whenever they feel like it or there
is a need for it. Those who indicated quarterly accounted for the least
percentage (2.8%).
Tab. 9
Frequency of Medical Treatment due to
Exposure to GHGs Emission
|
Frequency |
Frequency |
Percent |
|
Daily |
121 |
21.9 |
|
Weekly |
90 |
15.5 |
|
Monthly |
51 |
8.8 |
|
Quarterly |
16 |
2.8 |
|
Whenever I
feel like |
302 |
52.0 |
|
Total |
580 |
100.0 |
Similarly, the study also sought from the
respondent the percentage of monthly income spent on medical treatment due to
the exposure to GHG emissions from transport operations. It is worth knowing
that Table 10 revealed that the majority (50.0%) of the respondents do spend
between 10 and 20 per cent of their monthly income on medical treatment. This
is followed by 21 to 30 per cent (20.0%), while three per cent (3%) of the
respondents do spend above 50%. This may be the result of an underlying health
condition.
Tab. 10
Percentage of Income Spent on Medical Treatment
due to
Exposure to GHG Emissions
|
Frequency |
Frequency |
Percent |
|
Less than
10% |
58 |
10.0 |
|
10% -20% |
290 |
50.0 |
|
21% - 30% |
116 |
20.0 |
|
31% - 40% |
41 |
7.0 |
|
41% -50% |
29 |
5.0 |
|
Above 50% |
17 |
3.0 |
|
Total |
580 |
100.0 |
4.5.2. Measures to Reduce GHG Emissions from Transport
Operations
Transport operations in developing countries, particularly Nigeria, are
characterized by a number of externalities, including GHG emissions, as a
result of underlying issues such as poor administrative functional
configuration, institutional framework, and policy implementation. This has a
general impact on the performance of the transportation system as well as its
unprecedentedly high contribution to public health pollution; as a result,
efforts to minimize or eliminate this menace should be accelerated across
Nigerian cities, particularly the capital cities. In a bid to understand the
measures possible to address this identified menace, this subsection
investigated the effective measures to reduce the GHG emissions associated with
transport operations in the study area (Table 11). Results in Table 11 show
that a majority of over 70% (5 of 7) of the measures ranked above the MIV of 3.3926,
indicating effective ways of reducing GHG emissions from the poorly regulated
transport operations in the study area. Specifically, measures such as the need
to strengthen the awareness campaign (3.7629), the establishment of a periodic
advocacy programme (3.6426), strengthening vehicle service maintenance and
strengthening the implementation of transport policy (3.6065), and
strengthening the implementation of standards for automobile industries
(3.4605) were ranked first, second, third, fourth, and fifty-first,
respectively.
Tab. 11
Measures to Reduce GHG Emissions from Transport
Operations
|
Measures |
SD |
D |
A |
SA |
TWV |
RIM |
MIV |
RK |
|
Strengthening the awareness campaign |
12 |
38 |
174 |
1964 |
2190 |
3.7629 |
3.3926 |
1 |
|
Establish a periodic advocacy programme |
10 |
16 |
468 |
1624 |
2120 |
3.6426 |
2 |
|
|
Strengthening vehicle service maintenance |
33 |
76 |
144 |
1844 |
2099 |
3.6065 |
3 |
|
|
Strengthening the implementation of standards
for automobile industries |
32 |
80 |
396 |
1504 |
2014 |
3.4605 |
4 |
|
|
Provision of test facility centers with
affordable corrections materials |
22 |
324 |
309 |
1172 |
1829 |
3.1426 |
5 |
|
|
Implementation of the transport policy |
33 |
76 |
144 |
1844 |
2099 |
3.6065 |
3 |
|
|
Strengthening the provision and use of
alternative energy vehicles, e.g., electric cars and buses |
34 |
174 |
807 |
760 |
1595 |
2.7405 |
6 |
5. CONCLUSION AND RECOMMENDATIONS
The prevalent
surge in accessibility and mobility needs for both individuals and freight,
coupled with the inadequate state of technologically advanced transport
infrastructure and the government's lackluster approach at federal, state, and
local levels to provide consistent and quality public transport systems, has
resulted in increasing car ownership, the widespread use of vehicles dependent
solely on fossil fuels, and excessive reliance on road modes in Nigerian
cities. This dependence, during operations, leads to the release of greenhouse
gases (GHGs) into the environment, exerting adverse effects on the climate. The
lifestyle and behavioral patterns of motorists, particularly in the utilization
of personal vehicles for daily transport and logistics, significantly
contribute to the excessive release of CO2 into the environment.
This, in turn, manifests in noticeable variations in temperature,
precipitation, radiation, and wind speed in urban areas.
Given the
indispensable role of transport operations in socio-economic activities and
national development, it is imperative to ensure that these operations align
with environmental norms to mitigate the adverse impacts that have contributed
to recent climate change. The urgent need to mitigate the existing global
warming and address climate challenges resulting from escalating transport
activities, along with the quest to reduce excess CO2 in Nigerian
cities, underscores the importance of continuing advocacy and strategic
planning of the transport system. In light of these considerations, the study
investigates the influence of transport on the evolving local climate in
Nigeria's southwestern capital cities. The findings reveal that the impact of
the local climate changes induced by transport operations is extensive and
obvious across the sampled capital cities, adversely affecting the quality of
life, socio-economic functions, and overall sustainability of the cities. To
curtail the contribution of transport operations to greenhouse gas emissions
and mitigate their adverse effects on local climate and health in the study
area, the study proposes the following recommendations:
§
The need to strengthen
the awareness campaign through the establishment of a periodic advocacy
programme for motorists not only in the capital cities but across all urban
areas within the southwestern part of Nigeria.
§
The need to strengthen
vehicle maintenance services and the implementation of transport policy.
Motorists need to be educated on the importance of periodic and regular vehicle
maintenance services, particularly for their health. Meanwhile, there should be
provisional test centers with strict policy implementation.
§
In the
automobile transport industry, there should be strict adherence to standards in
facility provisions and operations.
§ There is a crucial
need to strengthen the adoption and provision of conventional mass public
transport systems, particularly electric or solar-powered vehicles like
trolleybuses, trams, and light rails, especially for intercity operations.
§ Simultaneously, there
is a pressing need for an effective and formidable transport institutional and
administrative framework with policies to effectively regulate transport
operations and curb greenhouse gas emissions from transport operations. These
mitigation strategies encompass demand-side initiatives aimed at minimizing
physical movement through thoughtful complete street models and inclusive land
use planning, implementing user fees for parking, and enforcing fuel taxes.
These complementing supply-side initiatives that involve deploying
energy-efficient and dedicated mass transit systems for the public and
coordinating land use with transport services will lessen environmental
degradation and climate challenges and promote sustainable development in the
study area and areas with similar challenges.
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Scientific Journal of Silesian University of Technology. Series
Transport is licensed under a Creative Commons Attribution 4.0
International License
[1] Department of Urban and Regional Planning,
Olabisi Onabanjo University, Ago-Iwoye, Nigeria.
Email: obafemiumar@gmail.com. ORCID: https://orcid.org/0000-0003-1630-3420
[2] Department of Urban and Regional Planning,
Olabisi Onabanjo University, Ago-Iwoye, Nigeria.
Email: simeonfash43@gmail.com. ORCID: https://orcid.org/0000-0003-4989-0019
[3] Department of Urban and Regional Planning,
Olabisi Onabanjo University, Ago-Iwoye, Nigeria.
Email: tundeshodunke@gmail.com. ORCID: https://orcid.org/0000-0002-3218-6562
[4] Department of Urban and Regional Planning,
Oke-Ogun Polytechnic, Saki, Nigeria.
Email: ademolakanmu@gmail.com. ORCID: https://orcid.org/0000-0002-9264-5863
[5] Transport and Logistics Limited, Ibadan,
Nigeria. Email: sekinatmotunrayo@gmail.com.
ORCID: https://orcid.org/0000-0002-0713-4699
[6] Department of Transport Management Technology,
Federal University of Technology, Akure, Nigeria.
Email: lovesamo001@gmail.com. ORCID: https://orcid.org/0000-0002-3218-6562