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Analysis of the Impacts of Microbes on External Building Wall Finishes in Enugu urban Environment

Iloeje, A. F, Isiofia, L. A.; and Aniagolu, C. O.

Faculty of Environmental Sciences,Enugu State University of Science and Technology, Agbani

ARTICLE INFO

Article history: Received 20th feb, 2018 Received in revised form 30th Feb, 2018 Accepted march 27th, 2018 Available online 10th August 2018

ABSTRACT

The impact of microbes on external building finishes was examined in this paper. Eighteen impact indicators were identified and categorized under so-cial, economic, structural and environmental factors. Survey research method was adopted in which questionnaire was used as the instrument to elicit infor-mation from selected respondents using purposive sampling technique. De-scriptive and Inferential Statistical tools were equally used for data analysis. Two hypotheses were postulated to test the relationships existing between the vulnerability conditions and the social, economic, structural and environmen-tal consequences. The resulting relationships were represented by the struc-tural equation model. Strong relationships were seen to exist between the independent variables (vulnerability conditions) and the dependent variables, showing that the microbes have significant impact on the external building finishes in Enugu urban. There exist positive and significant relationships with standardized coefficient of 0.317, P < 0.05, and 0.178, P < 0.05 for the social and economic consequences respectively; 0.376,P < 0.05, and 0.187, P < 0.05 for environmental and structural consequences respectively. The pa-per, therefore recommends a more aggressive research on building materials production to create microbe-resisting finishing materials that will check-mate the deleterious effects of the activities of these microbes on building surfaces.

Keywords: Economic Environmental Impact Microbes Social Structural.

Corresponding Author

E-mail Address: get2frankfast@gmail.com 07038968006 https://doi.org/10.36265/rejoen.2018.010111

.

ISSN - 1597 - 4488 publishingrealtime.

All right reserved.

1. Introduction

Microbes exist almost everywhere within the biosphere, and their activities can either be detrimental or beneficial to the environment on which they grow. It is common, in tropical rainforest areas, to see building facings changing colorations not actually due to wearing out of the materi-als as a result of age, but due to some greenish, some-times blackish coating appearing on the surfaces, thus defacing the wall. The spores of molds and bacteria are most times airborne thus making them ubiquitous and

therefore can equally be indoors. When they settle on building surfaces, their interactions with the building ma-terials generally result in bio deterioration of the material playing host to the microbe. All types of building materi-als can deteriorate as a result of microbial action (Scherer, et al., 2009). The rate of deterioration depends on the ma-terial used, construction technique employed, properties and behavior of the material, the climatic condition of the environment and the use of the building of which the ma-terial is in service (Isiofia, 2004). The climate determines which microbes will mainly grow. The rain and the wind

Iloeje, et al. rejoen 11, 2018, 96-101

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favour the transport of microorganisms. The orientation of facades also impacts on the biological development. An ex-posure toward the North will be characterized byan absence of sunand consequently high humidity. These conditions favour the biofouling (Barberousse, 2016). Organic materi-als such as paints, polymers and mineral materials such as mortar, concrete, natural stones or clay bricks are sensitive to bio deterioration (Grosseau, Estelle, Christine, Ren´e and Denis, 2015). Humid conditions have been implicated as creating the enabling environment that largely encourages the growth and subsequent multiplication of these microbes on the exposed building surfaces. Gaylarde and Morton (1999), opined that virtually all damp surfaces in buildings, including concrete, stone, brick, plas-ter, wood, plastics, painted surfaces or metal, may become colonized by microbial cells settling from the air. The colo-nizing microbes are bacteria, fungi and some algae and to-gether with the products of their metabolism, such as acids and polymeric materials, they form a biofilm, which can trap particulate materials, thus increasing the disfiguring effect of the biofilm.Grosseau, et al(2015), showed that the coloniza-tion of building facades by microbes is the main cause of their aesthetical deterioration. The ageing of facades causes a change of the state of the surface which further favors the development of these species, particularly in places where rainwater flows, and more pronounced where the flow is sluggish. Saiz-Jimenez (1997), Warscheid and Braams (2000), showed that the host’s environment conditions the type of microorganism which colonizes a façade and goes further to determine the degree of impact of these microbes. The deterioration of buildings is made faster by the activities of these microbes on exposed surfaces and diminishes the overall scenic beauty of the environment. This study therefore examined the impact ofthe activities of microbes on external building surfaces and went further toi-dentifythe relationships between the vulnerability conditions and thesocial, economic, structural and environmental con-sequences.To address this, the following impact indicators were outlinedand categorized: SOCIAL: Loss of aesthetics, Reptile infestation, Building decay, Reduction in scenic beauty, discoloration of surfaces; ECONOMIC: Frequent building maintenance, High mainte-nance cost, Loss of fund, Reduction in life span; STRUCTURAL: Reduction in strength of material, Induced surface cracks, Depletion of sensitive surfaces; Loss of fric-tional properties, Increased ageing process; ENVIRONMENTAL: Damp retention, Excessive/High hu-midity, Adverse health impacts, Unpleasant odor. Twonull hypotheses were postulated to test these relation-ships. Ho: there is no significant relationship between the vulnera-bility conditions and the social and economic consequences of microbes on external building finishes in Enugu urban. Ho: the vulnerability conditions do not significantlyinflu-ence the environmental and structural consequences of mi-crobes on external building finishes in Enugu urban. 2. Methodology

Survey research method was adopted for this research. The population of the study was based on houses located in Enu-gu metropolis covering low density (Independence Layout) and high density (Abakpa Nike) areas while the units of analysis were owners of houses. The population of the stud-ied houses was not known which informed the need for the use of sample size formula for infinite population derived from z distribution which resulted in sample size of 515 where n is the sample size, p is probability of success, q is

the probability of failure, z is the standard score correspond-ing to a given confidence level, ande, is the proportion of sampling error. Purposive sampling technique was used for selection of respondents by the researcher to ensure that only the desired house owners that would be relevant to the study were accessed. 515 copies of structured questionnaire were distributed, however, 510 copies were completed and re-turned for the purpose of analysis.The questionnaire was split into two sections in which section A focused on demo-graphic details of respondents while section B focused on the constructs used in the study. Questionnaire was used as the measuring instrument to obtain information from the respondents. The measurement items in the questionnaire were designed using five point scale in which 5=Strongly agree,4=Agree,3=Undecided,2=Disagree and 1=Strongly disagree. The researcher and his assistants visited the target house owners in their houses. Also to ensure that the house owners were seen in their respective houses, the copies of the questionnaire were distributed during the evening of each day and weekends.

Descriptive and Inferential statistical tools were used to ana-lyze the data in which the demographic details were obtained using frequency tables, while further analyses, including inferential statistics, were performed using the structural equation modeling tool (with the aid of AMOS software version 18) which necessitated the estimation of Construct Reliability, Convergent Validity, Discriminant Validity, Model fit and test of hypotheses.

In the structural model used for the study, each construct comprises measurement variables. Thus, the constructs are:

EXPL: Explanatory construct (Vulnerability Conditions or Independent Variable)

SO: Social Consequences

ECO: Economic Consequences

EV: Environmental Consequences

ST: Structural Consequences

3. Results

The results reveal that among the gender of respondents, 284(55.7%) were of the male category while 226(44.3%) were females. Age range demonstrates that 136(26.7%) were within 18-25 years, 77(15.1%) were within 26-33 years, 116(22.7%) were within 34-41 years, and 116(22.7%) were within 42-43 years. Further, 65(12.7%) of the respondents were 50 years and above. Marital status shows that 294(57.6%) were married, 159(31.2%) were single, 37(7.3%) were widows, 6(1.2%) were widowers while 44(2.7%) were divorced. Regarding educational qualification, 31(6.1%) of the respondents had first school leaving certificate while 145(28.4%) had one or more of the following certificates: WASC/NECO/GCE. At the same time, 106(20.8%) obtained either NCE or ND certificate, 114(22.4%) obtained either BSc or HND certificate, 105(20.6%) had Master Degree, while 9(1.8%) obtained Ph.D. degree. In terms of occupa-tion, 50(9.8%) of the respondents were of the student/apprentice category, 109(21.4%) were self-employed, 73(14.3%) were private sector employees, 172(33.7%) were civil/public servants, 75(14.7%) were unemployed and 31(6.1%) were retirees.

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Table 1 Descriptive Statistics

3.1 Construct Reliability Five latent variables were estimated and measured using their respective reflective indicator variables. In table 2 the construct reliability was examined using composite

reliability values. All values of the CR were greater than 0.7 as recommended by Hulland (1999) as they range from 0.719 to 0.833. Thus, in terms of reliability, the scales were dependable.

Table 2 Construct Reliability

Construct Indicator Construct Reliability(CR) Average Variance Extracted(AVE)

Factor Loading

EXPL

EX1

EX2

EX3

EX4

0.739

0.421

0.794

0.544

0.679

0.544

ECO

EC1

EC2

EC3

EC4

0.719

0.402

0.721

0.707

0.660

0.389

SO ES1

ES2

ES3

0.769 0.527 0.795

0.683

0.694

EV EV1

EV2

EV3

EV4

0.833

0.556

0.789

0.724

0.758

0.708

ST EST1

EST2

EST3

0.751

0.505

0.832

0.599

0.682

Constructs N Mean Std. Deviation

EXPL 510 3.9497 0.71644

SO 510 3.9876 0.71230

EV 510 3.6917 0.69230

ECO 510 3.2333 0.85200

ST 510 3.4124 0.87212

Valid N (list wise) 510

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3.2 Convergent Validity

In the same table 2 above, the convergent validity was assessed using average variance extracted (AVE). Ac-cording to Fornell and Lacker (1981), the suggested benchmark is 0.5. As shown in table 2, this threshold was moderately satisfied. Hair etal(2006) recommended that a threshold of 0.3 should be marginally accepted. Interestingly, two constructs (EXPL and ECO) were below 0.5, but did not fall below 0.4. The remaining constructs were above the recommended 0.5 threshold. The convergent validity was further strengthened by the loading of 17 measurement variables out of 18 ranging from 0.544 to 0.832 except one(EC4) that had 0.389 loading.

3.3 Discriminant Validity

Inter construct correlation matrix in table 3 was used to assess the degree of discriminant validity that exists among the constructs .The correlation values between the constructs were less than 0.8, thus, they met the threshold recommended by Fraering and Minor(2006) suggesting the existence of discriminant validity, mean-ing that 100% correlation is absent between the con-structs. Thus, the constructs were found to be unique respectively.

Table 3 Inter-Construct Correlation Matrix

3.4 Model Fit

As shown in table 4, the model fit threshold for the indices

were satisfactory, thus, the result of the analysis of the study can be relied upon.

Table 4 Model Fit Analysis

Table 5. Hypotheses

EXPL ECO SO ST EV

EXPL 1 . .

ECO 0.641 1 .

SO 0.532 0.560 1 . .

ST 0.568 0.553 0.507 1 .

EV 0.587 0.536 0.505 0.517 1

Model Fit Acceptable Threshold Study Threshold Acceptable/ Non Acceptable

Comparative Fit Index( CFI) >0.9(Hu &Bentler, 1999) 0.913 Acceptable

Goodness of Fit Index(GFI) >0.9(Hooper et al. ,2008) 0.901 Acceptable

Parsimony Fit(PRATIO) Close to 1(Marsh &Balla,1994) 0.899 Acceptable

Root Mean Square Error of Approxima-tion(RMSEA)

<0.08(Hu &Bentler, 1999) 0.052 Acceptable

Relationship Standardized Estimate Unstandardized Estimate P Value

EXPL - SO 0.317 0.436 0.000

EXPL - EV 0.376 0.403 0.000

EXPL - ST 0.187 0.255 0.000

EXPL - ECO 0.178 0.228 0.000

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Figure 1Structural Model (Unstandardized Estimate)

Hypotheses Testing is shown in table 5 and represented by the structural model in figure 1.

The first hypothesis posits that there is no relationship be-tween vulnerability conditions and social and economic con-sequences of microbes on external building finishes in Enu-gu metropolis. The results show a positive and significant relationship with standardized coefficient of 0.317, P< 0.05,and 0.178, P < 0.05 for the socialand economic conse-quences respectively. The conclusion therefore is that the statistical evidence used in this study substantiates that there exists a strong and positive relationship

The second hypothesis claims that the vulnerability condi-tions and the structural and environmental consequences of microbes on external building finishes in Enugu metropolis are not related. The results show that the relationship is posi-tive and significant with standardized estimate of 0.376, P< 0.05, and0.187, P < 0.05 respectively. The conclusion there-fore is that the relationshipsare significant, given the statisti-cal evidence of the study.

4. Discussion of Findings

The demographic analysis showed that the gender distribu-tion of the respondents reflects the true picture of the house ownership structure characteristic of Enugu urban where a

greater percentage (55.7%) of houses are owned by men. Fewer women build and own houses and what added to the percentage of houses owned by women (44.3%) are widows exercising ownership rights over their late husbands’ proper-ties. The high percentage of house owners (22.5%) and (26.5%) fall between 34 – 43 years and 18 – 25 years re-spectively. These houses are either owned by inheritance or found in high density neighborhoods with low cost tenement buildings. In terms of occupation, the highest percentage of house owners are civil/public servants (retired and serving), posting 33.7% and indicating, rightly too, that Enugu urban is purely a civil service community.

The study shows that external building surfaces experience deterioration due to microbial attacks and this is in line with the findings of (Scherer, et al., 2009). It was equally gath-ered from the study that the rate of deteriorationdepends on the material used, construction technique employed, proper-ties and behavior of the material, the climatic condition of the environment and the use of the building of which the material is in service (Isiofia, 2004). This is evident in the result of the hypotheses which present strong relationships between the vulnerability conditions and the social, econom-ic, structural and environmental consequences.When these microbes settle on building surfaces, their interactions with the building materials generally result in bio deterioration of

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the material on which they settle. Hypothesis 1 stated that there is a positive relationship between the vulnerability conditions and economic consequences of microbial attack on external building finishes in Enugu metropolis. The result of the hypothesis indicates a strong positive relationship and this is in line with the findings of Alukoet al (2013) which stated that a significant amount of fund, time and resources are being spent on maintenance and repair activities in solv-ing the defects arising from the activities of mi-crobes.Vupputuriet al(2013) posited that some bridge col-umns were being viciously eroded and susceptible to failure as a result of microbial colonization of the reinforced con-crete members thus confirming the result of the claim in hypothesis 2.The positive relationships identified in the so-cial and environmental impacts have been collaborated by the finding of Saiz-Jimenez (2014) which posited that throughout history, humans have used the most beautiful and durable stones for monumental buildings and that these monuments, sculptures and stony art exposed to microbes have deteriorated over the years. This scenario creates un-sightly, and aesthetically unpleasant environment.

5. Conclusion

Following the results of the analyses, humid environment encourages the growth and proliferation of microbes on ex-posed building surfaces. This phenomenon causes gradual, but persistent deterioration of the building finishesresulting in social, economic, structural and environmental problems. Since the rate of deterioration,occasioned by this microbial attack, depends onthe material, construction technique, prop-erties of the material and the climatic conditions, building finishes should be made with materials hostile to these mi-crobes and further studies are required to identify such fin-ishing material. Enugu urban, which generally fallswithin the hot humid zone, is exposed to the vulnerability condi-tions that enhance the growth and proliferation of these mi-crobes.Consequently, most exposed building surfaces will gradually, but continuously suffersome degree of deteriora-tion, thus reducing the life span of the affected building and creating the need for regular maintenance thereby increasing the burden of cost on house owners.

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