Domestic Electric Power Generator Usage and Residents Livability Milieu in Ogbomoso, Nigeria

Abstract

Incessant electric power failures have forced Nigerian residents into extensive use of electric power generator. This implicates a host of environmental livability glitches. This study therefore appraises the livability implications of domestic usage of electric power generators. The relative incidence of generator use was appraised. Residents’ livability was also assessed across the three recognizable residential densities of the city having 20 political wards. Out of the total 561, 56 urban blocks (10%) were sampled. A questionnaire was administered to 511 respondents using a multi stage approach. Noise dosimeter was used to measure the noise level. Likert scaling method was used in the transformation of ordinal data into ratio or interval data. Regression analysis was used to explain the relationship between the relative incidence of electric generator use (GUI) and the relative level of residents’ livability (RLI) in the study. A high level incidence of power outage (81%) was observed to have encouraged a high incidence (78.6%) of electric generator use. There was observed a reliable relationship between relative incidence of electric generator use and residents’ livability(R = -811, P = .000). Economic, health and social components (in the order of listing) are affected by the use of electric generators. The study thus recommends physical, environmental, legal and administrative resolutions to eliminate the negative effects of electric power generator use.

Full text

Environmental Management and Sustainable Development
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2017, Vol. 6, No. 1
http://emsd.macrothink.org
91
Domestic Electric Power Generator Usage and
Residents Livability Milieu in Ogbomoso, Nigeria
Akindele O. Akin
Department of Urban and Regional Planning
Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
Tel: 234-803-809-3456 E-mail: oaakindele37@lautech.edu.ng
Adejumobi D. O.
Department of Urban and Regional Planning
Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
Received: January 6, 2017 Accepted: March 7, 2017
doi:10.5296/emsd.v6i1.10941 URL: https://doi.org/10.5296/emsd.v6i1.10941
Abstract.
Incessant electric power failures have forced Nigerian residents into extensive use of electric
power generator. This implicates a host of environmental livability glitches. This study
therefore appraises the livability implications of domestic usage of electric power generators.
The relative incidence of generator use was appraised. Residents’ livability was also assessed
across the three recognizable residential densities of the city having 20 political wards. Out of
the total 561, 56 urban blocks (10%) were sampled. A questionnaire was administered to 511
respondents using a multi stage approach. Noise dosimeter was used to measure the noise
level. Likert scaling method was used in the transformation of ordinal data into ratio or
interval data. Regression analysis was used to explain the relationship between the relative
incidence of electric generator use (GUI) and the relative level of residents’ livability (RLI) in
the study. A high level incidence of power outage (81%) was observed to have encouraged a
high incidence (78.6%) of electric generator use. There was observed a reliable relationship
between relative incidence of electric generator use and residents’ livability(R = -811, P
= .000). Economic, health and social components (in the order of listing) are affected by the
use of electric generators. The study thus recommends physical, environmental, legal and
administrative resolutions to eliminate the negative effects of electric power generator use.
Keywords: Electric power generator, Basic utility, Pollution, Livability, Nigeria

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1. Introduction
The issue of electric power generation in Nigeria over the years is exasperating. The country
is experiencing the worst electric crisis among its contemporaries (World Bank, 2004);
currently generating 4,500 megawatts of power (for more than 180M population) as against
the needed 30,000 (15% of total power required). This put actual electrification at 2%
(Nanaghan, 2009). The major alternative that Nigerians shifted to is the use of electric power
generators. Nigeria therefore spends 15% of its annual budget to import diesel. Aside
commercial and industrial consumption, as at 2009; more than six million Nigerians owns
power generating set and spent a staggering ₦1.56 trillion ($13.35Million) to fuel them in a
year (Nanaghan, 2009). More than 85% rely on only generator costing average of 20M
further loss as variable cost. Businesses, manufacturers, and banks among others, spend
between 30-40% of their revenue on diesel to generating electricity. Electricity crisis remains
key infrastructural development bottleneck and livability hindrance today.
Combustion of fossil fuels is responsible for more than 75% of the increase in atmospheric
carbon dioxide (Chambers et al, 2000; UN, 2011). A major way of burning fossil fuel in
Nigeria after automobiles is through electric generator usage. It contaminates air, water, soil
material which interferes with human health, the good quality of life, and natural functioning
of the ecosystem. (Walker and Hay, 1999; Stansfeld, S.; Haines, M.; and Brown, B. 2000;
Wakefield, 2002;Schdmit, 2005; Oyedepo, 2012; Afolayan et al, 2014). Fine particulate air
pollutant is known to contribute to cardiovascular and lung disease, increasing the risk of heart
attacks and a heart-related death. (Pichot, 1992)). Bronchitis pneumonia, chronic respiratory
disease, lung cancer, heart disease, damage to the brain, nerves, liver, are also associated with
the pollutants from generators.( Passchier and Passchier, 2000). The unwanted sound from
generator can damage physiological and psychological health, causing annoyance and
aggression, hypertension, high stress levels, tinnitus, hearing loss, sleep disturbances, and other
harmful effects (Pichot, 1992, Kryter, 1994; Guy et al, 1999; Blumenthal, 2001; Schwatz et al,
2010; Seleye-Fubara et al, 2011). This study therefore analyses the significance of the usage of
electric generators in Ogbomoso Nigeria.
Electricity among other technologies has come to be an indispensable part of our
environment. Living without it can only be better imagined. Most other technologies are
functionless without electricity and hence, the end of use of electric power generator is not in
sight as there is no guarantee to get electricity from other sources. This leaves us with many
important questions: is the rate at which generators are been used not high enough to be
significant in environmental degradation? What are the real and imagined consequences of
the incessant usage of generators? In regions where the use of generators has become a
sine-qua-non, are there no measures that should be put in place as policy options to
checkmate the attendant consequences of generator use? How serious are the damages
already caused by generator use and what are the implications for the future? These and many
other pertinent questions would be answered in this study. Answering the questions is hoped
to fill certain gaps on how the energy sector competes with the natural environment and how
the problems so created may be abated.

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2. The Study Area
Ogbomoso (8o15iN, 4o14iE) is a medium sized city, the second largest in Oyo state Nigeria. It
locates at the border of the rain forest and the guinea savannah within the south-western
Nigeria. The city is traversed by the only road that connects the North from the southwest. It
is 51km and 53km from Ilorin and Oyo respectively. The city performs high order functions
including the fact that it is a University town. This evidences the land use diversification and
the necessity to use electric power in making ends meet for the avalanche of diversified
population.
Figure 1. Ogbomoso within West-Africa, Nigeria and Oyo State

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3. Methodology
Primary and secondary data were used. Out of the total (561), 56 (10%) urban blocks were
sampled across the three recognizable residential densities in the 20 political wards of the
town; and using a multi stage approach, a questionnaire was administered to 511 respondents
eliciting information on electric generator usage and residents livability. Air samplers were
used to investigate air pollution due to generator use. At each time, sequential multiple
sampler or automatic impingers was used to take samples for two hours. The sampling cycle
is activated by a clock mechanism. Air is drawn through the device by a motor driven pump
equipped with a filter to remove particulate matter. Following the collection, samples were
sent to the laboratory for analysis Noise decimeter was also used to A method reminiscent of
Likert scaling was used to scale ordinal data (Afon, 2003), making them amenable to
parametric testing. For each ward, the number of respondents multiplied by 4 is the maximum
point achievable from each variable. This was used to standardize the weighing of the
responses from the residents. The total score for each variable, divided by the maximum point
achievable multiplied by 100 becomes the standardized score for each variable. A mean
average was computed for use as general mean for all the variables on the table. Thus, each
composite figure is given by:
Where: N1, N2 and N3are the variables selected for scaling, d, e and m are the actual score of
the variables and D, E and M are the maximum point that may be scored by the variables.
Regression analysis was used to explain the relationship between usage of electric generators
and residents livability in the study.
4. Discussion of Findings
Electric power generators are extensively used in the study. The chi-square test (P value
= .103) suggests that there is no significant difference in the usage of generators across the
wards. However, there were relative differences in the incidence of electric generator usage
across the wards sampled. High density areas with a higher incidence of commercial and
industrial uses translating into high density, poorly maintained, smaller, soot producing
electric generators followed by the medium and then the low density areas. Low density area
residents have more silent, bigger and more maintained electric generators. So, the higher the
building and human density, the higher is the incidence of electric generator usage.

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Table 1. Incidence of Electric Power Generator Use.
Variable/wards
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
X2
Power Outage
48
37
38
38
40
39
33
45
45
44
43
44
45
41
40
45
45
43
46
44
.124
Gen Possession
78
62
71
74
84
72
71
96
81
81
92
77
64
72
83
81
86
87
71
89
.305
Use Regularity
51
54
48
45
52
57
54
49
48
45
44
52
51
56
55
49
48
52
53
50
.061
Work Hour/day
9
10
6
6
7
10
9
9
8
9
8
5
6
7
9
9
8
8
7
10
.052
Fuel used/day
5
3
2
7
4
5
6
5
5
4
10
5
5
4
8
6
7
9
5
6
.051
No in Building
1.7
1.4
1.8
1.4
1.6
1.4
1.3
1.1
1.1
1.2
1.6
1.2
1.6
1,3
1,4
1.4
1.6
1.3
1.4
1.1
.045
No of Gen Used
3
2
4
4
3
4
3
4
4
3
2
3
3
5
5
3
3
4
4
3
.068
Age (Month)
32
39
38
41
40
35
34
35
27
33
31
37
33
34
36
34
37
33
34
36
.002
Service Regularity
2
3
1
3
2
3
1
5
2
3
4
3
2
2
2
4
3
2
2
5
.051
Fuel type
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
.443
Distance to Building
0.8
0.5
0.8
0.9
0.7
0.8
0.7
2.5
0.9
0.6
0.5
0.7
0.8
0.6
0.9
0.8
0.5
0.6
0.9
1.7
.453
Domestic use
61
68
66
69
67
79
77
92
81
73
71
69
65
69
69
76
78
67
68
89
.133
Other use
39
32
34
31
33
21
23
8
19
27
29
31
35
31
31
24
22
33
32
11
.112
Mean
26
24.1
24
24.8
25.9
25.3
24.2
27.2
24.9
25.1
26
25.4
24.1
25
26.3
25.8
26.2
26.3
25.1
26.8
.114
Key: Akata-1, Alafia oluwa-2, Arowomole-3, Caretaker-4, Idioro-5, Ijeru-6, Ijeru2-7, Low cost-8, Odokoto-9,
Oke alapata-10. Adenike-11, Aaje-12, isale afon-13, agboyin-14, adiatu-15, high court-16, okelerin-17, sabo-18,
isaleora-19, papa alajiki-20
This magnifies the risk posed by electric generator usage especially in the high density areas,
as well as the connections between cities livability and equitable facility provision. Important
inference to be drawn includes a cautious densification in cities and more holistic basic
facility-urban development considerations. As cities gravitates towards compact city
development, caution needs being exercised on the level of preparedness in terms of the
availability and functionality of the required basic technologies and facilities. Inadequate
provision of sustainable electricity has the propensity to trigger complex environmental
problems as residents improvise for electric power on daily basis.
4.1 Residents’ Livability as a Result of Electric Generator Usage
The cost of purchasing electric generators, daily burning of fuel for a minimum period of
three hours, servicing of the electric generators and other subtle costs constrains residents to
spending 42.24% of their income only for the purpose of generating electricity for a brief
period in a day.

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Table 2. Residents’ Livability as a Result of Electric Generator Usage
Variables
Area%
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Socio-economic effects
Expenditure on fuel
24
26
24
23.5
26
25.5
23.5
28
26.5
22.5
24
26
24
23.5
26
25.5
23.5
28
26.5
22.5
Maintenance
11.2
27.4
20.4
27.5
20.5
13.4
23.8
24.9
22.9
22.5
11.2
27.4
20.4
27.5
20.5
13.4
23.8
24.9
22.9
22.5
Electrical damaged
17.5
21.5
23
20
17.5
20
18.5
21
13.5
18.5
17.5
21.5
23
20
17.5
20
18.5
21
13.5
18.5
Theft
21
25.8
19.4
20.6
24
18
19.7
25
20.9
20.9
21
25.8
19.4
20.6
24
18
19.7
25
20.9
20.9
% Income spent
42
33
35
35
43
37
35
46
39
39
42
43
35
25
43
27
25
26
19
19
Social effects
14
14
10
11.5
10
11
11
14
8.5
10
14
14
10
11.5
10
11
11
14
8.5
10
Economic effect
17.5
26.5
18
16
26.5
16
17.5
10
16
17.5
17.5
26.5
18
16
26.5
16
17.5
10
16
17.5
Environmental effects
Noise
35.6
35.5
26.4
30.3
0
29.9
36.4
0
27.9
31.2
35.6
35.5
26.4
30.3
0
29.9
36.4
0
27.9
31.2
Smoke
29.1
31.1
27.5
0
24.1
24.7
30.6
0
26.8
28.4
29.1
31.1
27.5
0
24.1
24.7
30.6
0
26.8
28.4
Wall defacing
26.8
59.3
26.8
0
42.3
14
11.2
0
15.4
17
26.8
59.3
26.8
0
42.3
14
11.2
0
15.4
17
Env effects
19
18.5
20
20
15
19.5
19.5
22
20.5
20.5
19
18.5
20
20
15
19.5
19.5
22
20.5
20.5
Health effects
electric shock
20.8
35.5
8.4
4.2
10.5
2.1
8.4
27.1
16.6
4.2
20.8
35.5
8.4
4.2
10.5
2.1
8.4
27.1
16.6
4.2
Nervous diseases
15.5
14.5
15.5
18.5
16
8.5
3.5
17
9.5
12.5
15.5
14.5
15.5
18.5
16
8.5
3.5
17
9.5
12.5
Smoke
3.8
26.7
9.6
18.2
19.2
6.8
2
25
5.8
23.1
3.8
26.7
9.6
18.2
19.2
6.8
2
25
5.8
23.1
Hearing Loss
0
41.7
0
8.4
16.7
4.2
0
20.9
0
0
0
41.7
0
8.4
16.7
4.2
0
20.9
0
0
Eye Irritation
25.9
20.8
16.8
24.6
20
16.2
16.8
18.7
20
19.4
25.9
20.8
16.8
24.6
20
16.2
16.8
18.7
20
19.4
Respiratory Infection
22.6
16.7
22.1
19.6
16.1
19
22
17.4
16.2
20.8
22.6
16.7
22.1
19.6
16.1
19
22
17.4
16.2
20.8
Throat Irritation
4.4
33.7
30.4
30.4
27.1
26
18.5
0
0
21.8
4.4
33.7
30.4
30.4
27.1
26
18.5
0
0
21.8
Asthma
27.4
22.1
23
0
24.4
23.7
25.8
38.7
4.2
27.4
27.4
22.1
23
0
24.4
23.7
25.8
38.7
4.2
27.4
Migraine
4
44
57
0
56
18
16
0
16
20
4
44
57
0
56
18
16
0
16
20
Nausea
31.2
19.2
24.7
0
22.5
21.1
29.3
0
29.1
27
31.2
19.2
24.7
0
22.5
21.1
29.3
0
29.1
27
Dizziness
15
39.8
30.2
0
24.6
13.3
22.6
0
13.3
28.5
15
39.8
30.2
0
24.6
13.3
22.6
0
13.3
28.5
Fatigue
19.4
32.2
38.7
0
25.8
9.6
6.4
10.2
0
35.5
19.4
32.2
38.7
0
25.8
9.6
6.4
10.2
0
35.5
Coma/death
37.2
25.8
18.2
0
21.9
14.4
33.4
0
25.8
25.8
37.2
25.8
18.2
0
21.9
14.4
33.4
0
25.8
25.8
Lead Poisoning
0
60
33.3
0
33.4
16.7
6.6
0
0
0
0
60
33.3
0
33.4
16.7
6.6
0
0
0
Eye problem
8.4
71
50
0
62.5
0
0
0
0
0
8.4
71
50
0
62.5
0
0
0
0
0
Insomnia
39.9
22.4
29.4
0
19.6
35
39.9
0
35.7
38.5
39.9
22.4
29.4
0
19.6
35
39.9
0
35.7
38.5
Effluence
27
35.1
43.2
28.8
13.5
14.4
18
21.6
0
0
27
35.1
43.2
28.8
13.5
14.4
18
21.6
0
0
Health effect
31.8
25.6
23.9
31.8
20.9
27.1
28.1
26.4
20.2
21.4
31.8
25.6
23.9
31.8
20.9
27.1
28.1
26.4
20.2
21.4
Electricity Regularity
9
6.5
18.5
6
4
12.5
9.5
21
5
9
9
6.5
18.5
6
4
12.5
9.5
21
5
9
Frequency of Use
23.5
25.5
25
20.5
26
26.5
24
20.5
23
20.5
23.5
25.5
25
20.5
26
26.5
24
20.5
23
20.5
Sources: Author’s field work, 2016.
Akata-1, Alafia oluwa-2, Arowomole-3, Caretaker-4, Idioro-5, Ijeru-6, Ijeru2-7, Low cost-8, Odokoto-9, Oke
alapata-10.
Adenike-11, Aaje-12, isale afon-13, agboyin-14, adiatu-15, high court-16, okelerin-17, sabo-18, isaleora-19,
papa alajiki-20

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These impoverish users and create various other problems for them. Usage of electric
generator is a strong contributor to high poverty level in our cities. This is a serious livability
problem. Generator produces loud noises (an average of 58.2db) that are difficult to tolerate
exceeding the maximum safe outdoor noise level of 55db (WHO,1986). The situation
becomes worse with multiple generators within a plot size and worse still, a higher density of
electric generators within a unit space. One sample t-test revealed a significant difference (at
α = .01) between the WHO stipulated standard for the tolerable outdoor noise level and the
mean averages of the ambient noise levels obtainable from the areas sampled.
Table 3. Ambient Noise Level from Generators at Distances (Decibel)
Distance
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Mean
3m
82
83
82.8
86
85
84
84
72
84
83
84
84
81
81
80
84
85
86.7
78
78
84.6
6m
79
78.9
80
79
78
79
78
77
78
78
79
78
78
78
79
78
79
79
78
76
78.7
9m
72
71
71.3
72
72
71
72
69
72
72
72
72
72
72
72
72
72
71.3
72
70
71.3
12m
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65
65.5
15m
60
60.4
59.8
60
60
59
60
59
60
60
60
60
59
59
60
59
60
59.7
60
59
59.7
18m
55
54.4
54.4
54
55
54
55
52
54
54
54
55
55
54
54
55
55
54.4
55
52
54.2
21m
49
49.2
49.3
49
49
49
49
48
49
49
50
49
49
50
49
49
49
49.1
50
48
49.1
24m
45
44.2
44.6
44
45
45
44
44
45
45
45
45
44
44
44
45
45
45
45
44
44.6
27m
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
38.7
30m
35
35
35
35
35
35
35
34
35
35
35
35
35
35
35
35
35
35
35
34
34.8
Mean
58
58
58
58
58
58
58
55
58
58
58
58
58
58
58
58
58
58
58
56
58.2
Source: Author’s Field Survey, 2016
Akata-1, Alafia oluwa-2, Arowomole-3, Caretaker-4, Idioro-5, Ijeru-6, Ijeru2-7, Low cost-8, Odokoto-9, Oke
alapata-10.
Adenike-11, Aaje-12, isale afon-13, agboyin-14, adiatu-15, high court-16, okelerin-17, sabo-18, isaleora-19,
papa alajiki-20
Noise was found to be a function of distance. It varies inversely with distance with a negative
correlation of 0.851. The coefficient of determination (R2 = 0.996) posits that there is a high
degree of overlap between the two. In essence, putting the electric generator far away from
where humans stay or sleep during its use would solve the problems causable by noise.
Abatement method to alleviate the effects of generator use may look simple until we are
confronted with the standard plot sizes and multiple plot arrangement. In other words, an
average high density standard plot would be too small to buffer a single electric generator
effectively, if only distance is factored into the buffering. The situation becomes worse with
multiple generators within a plot of such size. Again all the adjoining plots that houses
residential units may have similar situation. This ultimately increases the density of .electric
generators within a relatively small area.
The implication of this can be much. Individual efforts alone may not be sufficient to buffer
away both the noise and fumes originating from multiple electric generators coming from all

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directions within the neighborhood. Understanding of the wind movement and cohesive
collaboration of the neighborhood residents in partnership with governmental solution can go
a longer way to mitigate the problems of noise and fumes. Conscious environmental greening
in terms of tree planting, adequate open spaces, parks and gardens which may increase the
carrying capacity of the environment would assist in the local carbon capture and
sequestration to deliver a better livable environment.
4.2 Air Quality Implications of Generator Usage
Complete or incomplete combustion of gasoline produces: carbon monoxide (CO), hydrogen
cyanide (HCN), hydrogen sulphide (H2S), hydrogen fluoride (H2F), Nitric oxide (NO),
Nitrogen dioxide (NO2) and Sulphur dioxide (SO2). Nevertheless, in this study, only carbon
monoxide, nitric oxide and Sulphur dioxide were investigated.
Table 4. Tolerable Standard and Observed Average Air Pollutant Concentration
SN
CO (mg/m3)
SO2 (mg/m3)
NO2 (mg/m3)
Medium
Max
Observed
Max
Observed
Max
Observed
Exposure
Source
1
Outdoor
0.573
27.32
8.98
0.0085
4.85
-
Average
2
Ambient
3.44
-
-
8hr
US/EPA
3
Outdoor
7
-
0.004
24hr/yr
WHO
4
Outdoor
10
-
-
8hr
WHO/EC
5
Outdoor
30
350ug/m3
-
1hr
WHO
Source: Adapted from Donney, (2011); ETC/ACM (2011)
The maximum environmental standard approved by the WHO for NO2 is 0.0085mg/m3. The
mean observed concentration of NO2 in the study was 4.85mg/m3. Similarly, against the
environmental standard of 7mg/m3, 27.32mg/m3 of CO was observed. The standard for SO2 is
0.0035mg/m3, but the mean average in the study was 8.98mg/m3. Volatile organic compound
was also high. The maximum tolerable level is 1.9ppm, a high mean average of 134ppm was
recorded (see table 5). Some ambiguity surrounds the measurement of hydrogen sulfide in
that it is also a byproduct of biological decay such as from solid wastes. The mean average
for the study is 1.98mg/m3. The result of t-test depicts a significant margin between the
maximum tolerable standard and the observed level of gas pollutants emitted from electric
generators during their use at alpha of .05. This implies that the ambient air pollution caused
by the usage of electricity is far above what human health can cope with over a long period.

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Table 5. Effluence from Electric Generator (mg/m3)
Area
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
SO2
8.9
9.2
8.9
9.8
9.1
9.1
9.8
8.9
9.0
9.2
8.9
9.3
9.2
9.8
8.9
8.9
9.8
9.8
8.9
8.2
NO2
4.9
5.2
4.9
5.8
5.1
5.1
5.8
5.9
5.0
5.2
4.9
5.3
5.2
5.8
5.9
4.9
4.8
4.8
4.9
4.2
CO
29
28
28
27
27
29
28
25
27
28
29
27
27
28
27
29
27
27
28
24
H2S
2.2
2.3
2.8
2.7
2.4
2.2
2.3
1.7
2.1
2.1
2.2
2.3
1.9
1.9
2.1
2.1
1.9
1.9
2.1
1.8
VOC
141
138
134
135
134
139
134
115
133
141
134
138
136
137
132
141
136
139
138
118
Source: Author’s Field Survey, 2014
Akata-1, Alafia oluwa-2, Arowomole-3, Caretaker-4, Idioro-5, Ijeru-6, Ijeru2-7, Low cost-8, Odokoto-9, Oke
alapata-10.
Adenike-11, Aaje-12, isale afon-13, agboyin-14, adiatu-15, high court-16, okelerin-17, sabo-18, isaleora-19,
papa alajiki-20
Cause-effect relationships that are well known includes the darkening of paint by hydrogen
sulfide; the damaging of vegetation by sulfur dioxide, oxidants, fluorides, and ethylene; and
the effect of carbon monoxide on the oxygen-carrying capacity of the blood (Katz, 1969).
Sulfur dioxide is one of the principal contaminants that may cause eye irritation and
respiratory tract infection. Visibility impairment is most likely to be caused by high
concentration of soot or smoke particles, dust or photochemical aerosols in the atmosphere
(Afolayan et al, 2014). Coping with regular use of electric generator is tantamount to taking a
regular high dosage of slow poison. The health-related dangers of carbon monoxide poisoning
as a result of operating electrical generators indoors were poorly appreciated, even by health
workers. There is a need for wider public education on the subject in Nigeria, and especially in
the mass media and at schools and hospitals (Afolayan et al, 2014).
5. Treatment of Variables
In all, 39 scaled variables were subjected to factor analysis (table 6). There were five linear
composites generated out of which three were considered residual as they account for similar
variables but with lower communalities. Generator Use Index (GUI) extracts 39.17% of the
total variance of the data set. The variables that load highly under it are: fuel type (.995),
incidence of power outage (.995), number of generator in a building (.992), Domestic use
(.992), Regularity of electric generator use (.991), Distance of generator to building (.990),
etc. Residents Livability Index (RLI) extracts 31.42% variance of the data set. The

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Table 6. Extracted Factors
SN
Variables
Factors
1
2
1
Power Outage
.992(3)
2
Gen Possession
.957(9)
3
Use Regularity
.991(4)
4
Work Hour/day
.983(7)
5
Fuel used/day
.986(6)
6
No of Gen in Building
.992(3)
7
Gen Age (Month)
.951(10)
8
Gen Service Regularity
.982(8)
9
Fuel type
.995(1)
10
Gen Distance to Building
.990(5)
11
Domestic use
.993(2)
12
Other use
.758(14)
13
Expenditure on fuel
.887(12)
14
Maintenance
.888(11)
.
15
Electrical appliance damaged
.996(1)
16
Theft
.764(24)
17
% Income spent on Generator
.960(9)
18
Social effects
.995(2)
19
economic effect
.981(7)
20
Noise
.972(8)
21
Smoke
.983(6)
22
Wall defacing
.943(11)
23
electric shock
.882(13)
24
Nervous diseases
.921 (14)
25
Hearing Impairment
.801(22)
26
Eye Irritation
.813 (17)
27
Respiratory Tract Infection
.811(18)
28
Throat Irritation
.942(12)
29
Asthma
.984(5)
30
Migraine
.956(10)
31
Nausea
.986(4)
32
Dizziness
.926(13)
33
Fatigue
.814(16)
34
Coma/death
.822(15)
35
Lead Poisoning
.798(23)
36
Eye Impairment
.803(21)
37
Insomnia
.988(3)
38
Effluence
.806(20)

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39
Health effect
.808(19)
Source: Author’s Computation, 2014
variables involved are: electrical appliances damaged (.986), social effects (.984), incidence of asthma (.956),
dizziness (.942), fatigue (.926) etc.. The study therefore used the two indices above to study the relationship
between the usage of electric generators and residents livability.
6. Relationship between Generator Usage and Residents Livability
The regression coefficient for GUI when regressed with Residents Livability Index (RLI) was
-811. This reveals that GUI is important to the explanation of residents environmental
Livability. In other words, there is a significant relationship between a livable environment
and the relative incidence of electric generator use. This implies that, when it is desired that
the environment be livable, one of the factors to be considered is adequacy of basic utilities
such as electric power, which may be negatively skewed towards the high incidence of
electric generator use. Fuel burnt, Power outage, regularity of domestic generator use,
multiple use of generators in a building, closeness of a working generator to where people are,
daily use of electric generator for a long number of hours and the use of old, poorly
maintained generators among others in the order of listing has been observed to relate
negatively to residents livability in the study.
Table 7. Summary of Regression Analysis
SN
Dependent
Independent
R
R2
F
P.Value
B
PValue
1
RLI
GUI
.-811
.658
19.011
.000
Constant
GUI
4.300
.535
.153
.000
Sources: Author’s computation, 2014.
Y= a + bx+ e ………… Regression Equation
Where Y = Dependent Variable (Residents Livability Index)
a = Constant (4.300)
b = .535 Regression coefficient of the relative incidence of generator use index (GUI)
Economic cost in terms of collateral damage of especially domestic electrical appliances, fuel
expenditure, the purchase and maintenance of electric generators are on top of the list of
electric generator induced livability problem. This is closely followed by the health problems
associated with the inhalation of fumes produced by these generators: insomnia, nausea,
asthma, migraine, throat irritation, and dizziness among others (see the ranking on table 6) in
the order of listing are the livability variables that the usage of generator has direct effects on.
The ability to improve environmental livability is relatively dependent on sustainable utility
provision. This is relative because other factors jointly contribute to environmental livability.
Invariably, the members of the linear composite of the relative incidence of electric generator
usage in the order that they have been listed are relatively important to the explanation of
Environmental livability. The inference for this study is that when areas are well supplied
with basic utility or services such as electricity in a sustainable way, they greatly enhance the

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economy, health and the social lives of the residents, thus; they have the chance of alleviating
environmental nuisances and environmental related diseases. To understand the degree to
which each of the linear composites of Relative incidence of electric generator use (GUI)
independently influence the linear composites of Residents Livability (RLI). The regression
model is calibrated. The equation is given by:
Y = a+bx (1)
Y= Residents Livability Index
a= Constant of the regression model
b= Coefficient of partial regression of the relative incidence of electric generator use
x = Relative incidence of electric generator use.
The coefficient for the model calibration is on table 7. Substituting for the equation therefore:
RLI = 4.3 + 0.535(GUI)
This equation implies that; holding other things constant, a unit increase in the index of the
relative incidence of electric generator use (GUI) will produce 0.535 decrease in residents
livability (RLI). But, residents livability in this study was basically measured by economic
efficiency of basic utility provision and its access by residents, absence of environmental
contaminants as a result of electricity provision, state of health of residents with a particular
concern for ailment which may arise from fuel combustion and pollutants produced by
electric generator during its use and the incidence of social problems such as crime, crowding
and other extrinsic effects of electric generator use. It thus follow that; decrease in the use of
electric generators would positively affect residents economic efficiency, improve their health,
alleviate environmental pollutants to reduce global environmental risks such as climate
change, carbon footprint and environmental morbidity and improve socio-psychological
balance in our cities.
6. Concluding Remarks
Electric generator usage is one of the most terrible human-induced threats to liveability in the
contemporary cities of the developing world especially Nigeria. It rightly commands
widespread policy and public attention. Along with other rapid changes associated with
global population and economic growth, climate change strains existing weak points in health
protection systems and calls for reconsideration of public health priorities. Exploration of
alternative electric power source is an imperative. Communities are advised to provide
sustainable electricity from ubiquitous environmental resources given their locals and
particulars. Sustainable monitoring and control of environmental standards that assures
quality air, city greening, noise abatement, water quality, temperature and so on should be put
in good priority. Legal and administrative frameworks needed for their proper enforcement
should be put in place.

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Acknowledgement
This is to acknowledge that this research was fully funded by the Senate Research Grant of
the Ladoke Akintola University of Technology, Ogbomoso Oyo State, Nigeria. The
participation of my students in the department of Urban and Regional Planning, LAUTECH
during the data collection is also acknowledged and appreciated.
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