Awareness of the effects of Small-Scale Cassava Mill Effluent on the Environment in Ika North East Local Government Area, Delta State, Nigeria

Awareness of the effects of Small-Scale Cassava Mill Effluent on the Environment in Ika North East Local Government Area, Delta State, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Awareness of the effects of Small-Scale Cassava Mill Effluent on the Environment in Ika North East Local Government Area, Delta State, Nigeria Matthew Ogorchukwu Isimah, Gladys Ogochukwu Chukwurah, Francis Ogochukwu Okeke, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6968127/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The awareness of the effects of small-scale cassava mill effluents (CME) on the environment in Ika Northeast Local Government Area, Delta State, was investigated. The study observed dying plants, contaminated water, and an unpleasant odor around cassava processing sites where CME flows indiscriminately on land. These are indications of environmental pollution that could affect the health and wellness of residents. The study used interviews and observation for data collection, and 399 questionnaires were administered to the respondents using systematic random sampling. A student t-test, ANOVA, and Pearson’s correlation were employed with SPSS version 21. The study revealed that most respondents had no in-depth knowledge of the implications of cassava effluent on the environment. This study shows no significant difference between males and females in awareness of the effects of CME on the environment (as the value of t = 2.267, P = .086). The result shows a significant variation in the awareness level of CME effects on the environment with age (P = .026, F = 4.014). There was a positive correlation between environmental awareness and education, occupation, and income. The study found that CME causes land degradation, air pollution, and water contamination. Therefore, the paper recommends an awareness campaign to educate the public on the implications of cassava effluent on the environment and the need for proper channeling and treatment before discharge for effective control and management. Environmental Policy Environmental Chemistry Behavioral Geography Cassava mill Effluent Environmental Effects and Pollution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Most third world economies are experiencing increased human population and Nigeria’s demographic change has been drastic (Okeke et al., 2020 ). With her fast-growing human population, the need for more food production is indispensable (Okeke et al., 2023). Cassava (Manihot esculenta) is a major staple food produced in the developing world, supplying food for over 500 billion people (Odoabuchi et al, 2020 ; Nwokoro et al., 2013 ; Abu et al, 2006 ). It was first cultivated in South America and introduced to Nigeria in the sixteenth century (Adeniji et al., 2005 ). Cassava is a perennial woody shrub, grown as an annual crop and serves as a cheap and rich source of carbohydrates, protein and vitamins A, B, and C when the leaves of the cassava are eaten as green vegetables (Eze and Nwibo, 2014 ; Omomowo et. al., 2015 ). Currently, the global production of cassava is about 215, 436, 496 out of these, Nigeria accounts for 20.6% being the largest producing nation (Izah et al, 2017 ; Izeh et al, 2018; Obueh and Odesiri-Eruteyan, 2016 ). The significance of cassava production in Nigeria in terms of food, employment, and source of income to farmers and the nation at large is not in doubt (Izah et al, 2017 ). However, the attendant effects of cassava mill effluent (CME) on the environment are challenging (Cumbana et al, 2007). Cassava effluent contains a high contaminating load of biological oxygen demand (BOD) and high cyanide content (Okunade and Adakalu, 2012) that can induce toxicological effects on the environments and its biotas such as humans, fisheries, flora, and fauna (Izah et al, 2018 ). Consequently, the CME discharge into the soil untreated prevents germination, inhibits plant growth, reduces plant yield, contaminates water bodies, and produces an offensive odor that disturbs the comfort of the populace (Izah et al, 2017 ; Nwaugo et al, 2008 ; Izah and Seiyaboh, 2018; Ezeigbo et al, 2014 ). Besides, Cassava wastewater ponds serve as a breeding point for mosquitoes that causes malaria, the commonest disease threatening lives in Africa where thirty countries in Sub-Saharan Africa account for 90% of global malaria deaths (The Nation Newspaper, 2018 ). The threat of environmental pollution in Nigeria particularly in Delta state is not only attributed to oil spills but as well as the discharge of cassava mill effluent which oftentimes is disposed indiscriminately. The boom of Cassava for multiple uses has attracted a lot of small-scale cassava processing factories sited around residential areas in Nigeria (Okechi et al, 2011 ), producing a large volume of cassava effluent with little or no attention to environmental pollution (Elijah et al, 2014 ; Nwaugo, 2008; Izah, 2018). Most millers that process and manage cassava mill industries do not have adequate knowledge of environmental safety, and the indiscriminate discharge of cassava effluent by farmers at the milling sites also suggests their slim understanding of the implications (Oghenejoboh, 2015 ). Interestingly, many researchers have studied the impact of cassava mill effluent on the environment in Nigeria. For instance, Obueh and Odesiri-Eruteyanm (2016) studied the “Effects of Cassava Processing Wastes on the Soil Environment of a local cassava mill in Ekiadolor, Ovia North East Local Government Area of Edo State, Nigeria”. Their findings showed that the continuous disposal of the cassava processing wastes in the soil environment around the mill and into a waste pit reduces soil quality and renders the environment polluted. Izah, et al ( 2018 ) researched the Impact of Cassava Milling Effluent in Nigeria and found that CME alters the quality of soil and water with regard to physicochemical, heavy metal, and microbial characteristics. Similarly, Chinyere et al., ( 2018 ) studied on Influence of Cassava Mill Effluent (CME) Dumping on Soil Physicochemical Parameters and Selected Plant Nutrients in Uturu, Abia State, Nigeria. Their findings showed that excess soil moisture of the CME-impacted soil is capable of limiting soil oxygen available to plants and thus alters microbial activities. But no study has focused on awareness of the effects of cassava effluent on the environment and no research on cassava effluent has been done in the study area. Consequent on these, being environmentally unaware could worsen the effects of CME on the environment. Hence, the need to investigate the demographic status, level and sources of environmental awareness of people on the effects of CME on the environment, and the factors influencing the choice locations of cassava processing sites to bridge the study gap. Ziadat ( 2010 ) opined that to better understand environmental attitudes, the level of knowledge possessed by the population under observation concerning the severity of environmental problems, and their reaction to and their interactions with nature must be ascertained by assessing environmental awareness. This has long been recognized in the more industrialized and developed nations of the world where many studies of environmental knowledge have been conducted over the last three decades (Constantini and Hanf 1972 ; Rauwald and Moore 2002 ). With this background, this study aimed at examining Awareness of the Effects of Small-Scale Cassava Mill Effluent on the Environment of Ika North East Local Government Area, Delta State, Nigeria, with the objectives of determining the demographic characteristics of the respondents, the level of awareness of the effects of CME on the environment in the study area, sources of awareness, factors that informed millers’ choice location of cassava processing site, and perceived effects of CME on the environment. Hypotheses There is no significant difference between male and female gender in awareness of the effects of CME on the environment among residents in the study area. There is no significant variation in the awareness of the effects of CME on environments in relation to age. There is no significant relationship between the awareness of the effects of CME on the environment and the socioeconomic status of residents in the study area. There is no significant relationship between awareness and sources of information about the effects of CME on the environment. 2.1 The Study Area Ika North-East Local Government Area lies between Latitude 6 0 07 1 47 11 and 6 0 19 1 07 11 N of the equator and between Longitude 6 0 10 1 25 11 and 6 0 22 1 37 11 E of the Greenwich meridian. It is bounded in the North by Edo State and Ika South Local Government Area. However, Ika South Local Government Area marks its Southern and Western limits, while Aniocha North and Aniocha South Local Government Areas marked its Eastern margin (Ugbomeh, 2011 ). Ika North East Local Government Area of Delta State occupies an area of about 463 km² with a population figure of 126,560 in 1991 with 61,303 males and 65,255 females (Eze and Nwibo, 2014 ; NPC, 2006, cited in Ugbomeh, 2011 ). The projected population of the area for 2022 is 272283. There are nine communities made up of Ika North East Local Government Area which include; Owa, Ute-Ogbeje, Ute-Okpu, Akumazi, Umunede, Idumuesah, Igbodo, Otolokpo and Mbiri (Eze and Nwibo, 2013) that spread out into fourteen wards in the area (Eze and Nwibo, 2014 ). The locations of these communities are indicated in the map of the study area as shown in Fig. 1. Generally, the terrain of Ika North East Local Government Area is characterized by undulating lowlands. The soils are sandy and loamy and are rich for agriculture and socio-economic activities. The environment has natural vegetation and water resources that support agricultural activities. The main occupation of the people is farming with cassava being the highest food crop produced and a major source of livelihood for the residents. The people are well known for “garri” production (cassava flakes) as shown in Figs. 1 & 2 . Materials and Methods This study employed both primary and secondary data to elicit relevant information. Primary data were sourced through structured questionnaires, informal interviews, and personal observation in a small-scale cassava processing environment. A total of 399 questionnaires were administered to the respondents using systematic random sampling. The sample size was obtained from the 2022 projected population of the study area with the formula: n = N/{1+ (e) 2 }. Where: n = total sample size, N = total population of the study area, e = level of precision (0.05), and 1 = unity (a constant) (Yamane, 1969). The questionnaire comprised two sections: a demographic section (gender, age, marital status, education, and occupation) and section two with fourteen questions about awareness of environmental pollution by CME. The questionnaires were administered within the nine communities that made up the study area according to their sample sizes as shown in Table 1 . The sample size of each community was calculated with the formula: total sample size of the study area multiplied by the population of each community, divided by the population of the entire study area (Rilwani, 2005 ). The researchers employed the services of four indigenes for questionnaire administration. To ascertain the level of awareness of the effects of CME on the environment, respondents were told to tick appropriately the scaling of the awareness based on five Likert Scale items (1 = not aware, 2 = slightly aware, 3 = neutral, 4 = moderately aware, and 5 = extremely aware). The Likert scale is a non-comparative scaling technique and psychometric response scale which is used in surveys for the reason of obtaining the degree of agreement of respondents with a set of statements (Dane 2006 ). Interviews were conducted with ten owners/operators of cassava processing engines and nineteen 19 persons among the respondents to express their experiences and opinion regarding the effects of cassava effluents on the environment. Secondary data were obtained from journals, newspapers, textbooks, and other internet materials. The projected population of the study area for 2022 is 272283 using the extrapolation method p n = p o (1 + r) n Where p n = present population, p o = target population, n = number of year(s) for the last population and r = growth rate (Yamane, 1967 ; Rilwani, 2005 ). For this study, a 2.5% growth rate was used. Table 1 Population and Sample Sizes of Each Community in the Study Area. Community 1991 Census 2006 Projected 2022 Projected Sample Size Owa 48880 70792 105091 154 Mbiri 4875 7060 10481 15 Igbodo 9074 13142 19509 29 Umunede 21611 31299 46464 68 Akumazi 12368 17913 26592 39 Idumuesah 5652 8186 12152 18 Otolokpo 4990 7227 10729 16 Ute-ogbeje 4278 6196 9198 13 Ute-okpu 14915 21601 32067 47 Total 126560 183416 272283 399 The study used descriptive and inferential statistics to analyze the collected data through SPSS version 21.0. The descriptive analysis includes frequency tables, percentages, and charts. On the other hand, Student T-test, ANOVA, and Pearson’s Correlation were adopted to analyze the three stated hypotheses. The techniques are appropriate for this study as they checkmate the significant differences and relationships between two or more independent variables. Results and Discussion Demographic Characteristics of the Respondents Table 2 depicts the demographic characteristics of the sampled population of the study. Out of 399 sampled respondents, 27.6% of the respondents are male; while 72.4% are female which indicates that female was more involved among the participants. The findings show that 5.0% of the respondents are less than 18 years of age, while 42.4% of the respondents are between the age of 18–33 years. The majority of the respondents (45.1%) were between the age of 34 years to 49 years, and 7.5% of the respondents are aged 50 and above. Age is vital in any population as it determines the working force that contributes maximally to the socio-economic life of people. In terms of education, 19.3 percent of the respondents attended primary school, 70.1% secondary, and 10.1% tertiary institutions. The implication is that buck of the respondents who were equally farmers stopped their education in secondary school probably due to financial constraints as some voiced out during an interview. There was no record of unschooled. The highest percentages (75.1%) of the participants are farmers who solely rely on the income from the farm for their livelihood. The students (12.5%) who participated were second to the highest in terms of occupation. The business accounted for 7.5% of the respondents as against 4.8% of the civil servants who participated. None of the respondents indicated unschooled. The highest percentages (62.7%) of the respondents earn #20,000-#40,000 per month, followed by 24.1% of those who earn less than #20,000 per month. The next is 10.8% of those whose monthly take home was #61,000, while 2.5% of the respondents realized #41,000-#60,000 per month Table 2 Demographic Characteristics of the Respondents Demographic Characteristics Group Frequency Percentage (%) Gender: Male 110 27.6 Female 289 72.4 Age Less than 18 yrs 20 5.0 18–33 years 169 42.4 34–49 years 180 45.1 50 years and above 30 7.5 Level of Education Primary 77 19.3 Secondary 280 70.1 Tertiary 42 10.5 No Education - - Occupation Business 30 7.5 Farmer 300 75.1 Student 50 12.5 Civil Servant 19 4.8 Income < #20,000 per month 96 24.1 #20,000- #40,000 per month 250 62.7 #41,000 - #60,000 per month 10 2.5 #61, 000 and above per month 43 10.8 Awareness of the Effects of CME on the Environment The general knowledge of 399 respondents on the effects of cassava mill effluent on the environment was explored as shown in Table 3 . Though the effects of CME on the environment are not new to the respondents, the majority of the participants do not have adequate knowledge of its attendant effects. Results revealed 51.3% of the respondents indicated not being aware of some effects of CME on the environment in terms of land degradation, water contamination, and air pollution. About 0.5% of the participants were neutral (neither aware nor not aware). However, 7.5% of respondents have slight awareness, followed by 17.3% of the participant with moderate awareness, and 23.8% were extremely aware. From the data obtained, except questions 6 & 9 which recorded a high level of awareness, and questions 10 & 7 which indicated moderate awareness, all other ones were low. Having a general mean of 2.58 is an indication of low awareness of the effects of CME on the environment. Table 3 Result Responds to All Questionnaires. Question Total Number Answered Sentiment Level Mean Remark Not Aware % Slightly Aware % Neutral % Moderately Aware % Extremely Aware % Q1 399 28.1 33.1 0 25.1 13.8 2 Low Q2 399 89 5.0 0 4.5 2.0 1.3 Low Q3 399 81 7.0 1.3 5.5 2.3 1.4 Low Q4 399 52.6 12.5 0.5 26.8 7.5 2.2 Low Q5 399 89.2 5.0 1.5 4.3 0 1.2 Low Q6 399 0 0 0 9.8 90.2 5 High Q7 399 0 7.5 0 75.2 17.3 4 Moderate Q8 399 72 10.0 0.5 12.5 5.0 2 Low Q9 399 0 0 0 10.0 90 5 High Q10 399 0 0 0 15.0 85 4.3 Moderate Q11 399 90.5 2.5 2.5 2.5 2.0 1.2 Low Q12 399 12.5 24.6 0 50.4 12.5 3.3 Low Q13 399 64.2 10.0 0 16.0 9.5 2 Low Q14 399 90.5 1.5 1.8 2.5 1.3 1.2 Low Q15 399 100 0 0 0 0 2 Low Total 51.3 7.9 0.5 17.3 23.8 38.1 Grand Mean = 38.1/15 2.58 Low Sources of Awareness on the Effects of CME on Environmental Figure 4 constitutes the respondent’s sources of information on environmental pollution occasioned by CME in the study area. The finding shows that 3% of the respondents obtained knowledge of environmental pollution by CME from newspapers. Those who got information from TV are 9%, followed by 3% from the internet, 49% from friends, 35% from the community, and 1% from advertisements. It implies that buck of the knowledge on environmental pollution caused by CME in the study area, came from friends probably at the grating site where the effects are felt mostly, particularly the offensive odor. The implication is that the extent of awareness from a friend is predicated on the level of exposure of the person. Factors that Informed Miller's Choice Location of Cassava Processing Plants Fig. 5 shows the various factors that informed the miller’s choice of location of cassava processing machines in the study area. The highest factor as indicated by 35% of the respondents was the availability of land, followed by nearness to residential location as 19% of the respondents claimed. The respondents who choose nearness to farm road as a major factor are 18%. Other respondents who considered accessibility, proximity to a water source, and security were 17%, 6.0%, and 5.0% respectively. The study shows that factory owners did not consider the effects of CME on the environment before building their industry. None of the respondents considered government policy as a factor. Environmental Awareness and Socio-economic Factors Environmental concern is influenced by socioeconomic status. Oftentimes, those with high environmental awareness, have much concern for their environment, which is linked to several factors like educational background. Those with low socioeconomic levels think more about satisfying their immediate material needs than environmental issues. As such, considering socioeconomic factors is assumed essential in assessing the environmental awareness of any society. The awareness levels of the participants based on their socioeconomic status are presented in Table 4 . Table 4 Awareness Responds Based on Socioeconomic Factors Status Group Frequency Not Aware Slightly Aware Neutral Moderately Extremely Aware Gender: Male 110 10 40 5 41 14 Female 289 25 120 100 109 25 Age Less than 18 yrs 20 0 5 0 12 3 18–33 yrs 169 10 69 10 57 23 34–49 years 180 14 30 25 80 31 50 yrs & above 30 0 4 0 19 6 Education Primary 77 9 24 10 33 0 Secondary 280 20 105 18 112 25 Tertiary 42 0 8 0 14 20 No Education 0 0 0 0 0 0 Occupation Business 30 3 8 2 12 5 Farmer 300 40 82 30 128 20 Student 50 0 5 0 30 15 Civil Servant 19 0 4 0 10 5 Income < #20,000 per month 96 10 31 3 33 19 #20,000- #40,000 per month 250 30 100 14 67 39 #41,000 - #60 ,000 per month 10 0 4 0 6 0 #61, 000 and above per month 43 0 20 4 19 0 Gender Table 5 shows the level of awareness based on the respondents’ socioeconomic status. The male awareness follows in the order of 14 persons that are extremely aware, 41 moderately aware, 5 neutral, 40 slightly aware and 10 not aware. The awareness of females is in the order of 25 extremely aware, 109 moderately aware, 10 neutral, 120 slightly aware, and 25 not aware. To obtain more objective measures, the influence of gender on environmental awareness was determined, using a student t-test. The result revealed no significant difference between male and female gender in awareness of the effects of CME on the environment as the P-value is greater than a 95% level of confidence(t = 2.267, df = 4, n = 399. P = .086). The null hypothesis indicated in hypothesis 4 was rejected, while the alternative was accepted. It implies that gender is insignificant for the prediction of awareness level of the effects of CME on the environment in the study area. To some scholars, men are more active in education and social lives for a long time, as such, should be more concerned and knowledgeable about the immediate environment. But due to the quest to make more money to meet up his social responsibilities, ponder less on environmental issues (Ustun and B. Celep, 2007 ). Ballew et al. ( 2018 ) argued that average women are slightly more likely than men to be concerned about the environment and have stronger pro-climate opinions and beliefs. However, the result of this study showed no significant difference which contradicts the assertion of some scholars who posit a disparity between male and female gender in environmental knowledge (Al-Rabaani and Al-Shuili, 2020 ; Martínez-Borreguero et al, 2020 ). Additionally, an inferential analysis was carried out based on the age of the participants. The idea was to examine whether age could influence awareness of environmental pollution via cassava effluent. The ANOVA result shows that there is a significant difference in the level of awareness of the effects of CME on the environment in relation to age (P = .026, F = 4.014) at a 95% level of significance. This implies that age plays a significant role in the prediction of environmental awareness about cassava effluent pollution. Pearson’s product-moment coefficient was run to examine the relationship between awareness and socioeconomic status of respondents in terms of the effects of CME on the environment. The factors considered for the analysis are education, occupation, and income. The variables in Table 5 were used to examine the correlation. The results revealed a strong, positive correlation between environmental awareness and education/occupation/income (concerning the effects of CME on the environment) as stated in hypothesis 3, which were statistically significant (Between education and awareness, r = .808 ** , n = 399, p = .000; occupation and awareness, r = .819 ** , n = 399, p = .000; income and awareness, r = .865 ** , n = 399, p = .000). The summary of the result is in Table 5 . Table 5 Summary of Pearson Correlations EDUCATION OCCUPATION INCOME AWARENESS EDUCATION Pearson Correlation 1 .735 ** .891 ** .808 ** Sig. (2-tailed) .000 .000 .000 N 399 399 399 399 OCCUPATION Pearson Correlation .735 ** 1 .812 ** .819 ** Sig. (2-tailed) .000 .000 .000 N 399 399 399 399 INCOME Pearson Correlation .891 ** .812 ** 1 .865 ** Sig. (2-tailed) .000 .000 .000 N 399 399 399 399 AWARENESS Pearson Correlation .808 ** .819 ** .865 ** 1 Sig. (2-tailed) .000 .000 .000 N 399 399 399 399 **. Correlation is significant at the 0.01 level (2-tailed). Relationship between Environmental Awareness and Source of Information The pursuit of environmental sustainability is commendable, considering the rate of abuse of the natural resources in our environment. However, it requires continued environmental education to change the perceptions and attitudes of people towards the environment around us for sustainable development. The likelihood of obtaining adequate and reliable information depends on the sources of such information and the exposure of the disseminator. Udalov et al. (2021) opine that "different information sources might have different effects on environmental concern"; as a result, the study examines the relationship between awareness and sources of information about the effects of CME on the environment. Among the selected sources of environmental awareness, only the internet source recorded a moderate level, while the rest were low, as shown in Table 6 . Table 6 Level of Awareness on the Effects of CME on the Environment and Sources of the Information Source of Awareness Number of Response Sentiment Level Mean Remark Not Aware Slightly Aware Neutral Moderately Aware Extremely Aware Total Response. Newspaper 12 0 8 0 1 3 35/12 2.92 Low TV 36 0 27 0 4 5 95/36 2.64 Low Internet 12 0 2 0 3 7 51/12 4,25 Moderate Friends 195 0 167 0 21 7 453/195 2.32 Low Community 140 0 18 10 12 336/140 2.4 Low Advert 4 0 4 0 0 0 8/4 2 Low Total 16.53/6 2.76 Low Test of Hypothesis The Pearson correlation result showed a significant relationship between environmental awareness and source of information (r = -659, P-value = 0.0000), as presented in Table 7 . Since the P-value is significant at 0.01 confidence level, the null hypothesis, as stated in Hypothesis 4, was accepted. The significance is positive and strong. Therefore, the source of information should be considered a predictor in addressing environmental awareness. The result implies that, all things being equal, increases in the quality and reliability of information sources could increase people's knowledge of CME effects on the environment. In other words, the level of environmental awareness depends on sources of information. One would ordinarily expect that since the number of respondents from friends and the community is high, their awareness should have increased. However, the source of information determines public perceptions of the environment and the value of that information, which helps in shaping people's behaviours towards the environment. Table 7 Summary of Pearson Product Moment Correlation showing Relationship between Source of Information and Respondents’ Level of Awareness of the Effects of CME on the Environment AWARENESS SOURCES AWARENESS Pearson Correlation 1 − .727 ** Sig. (2-tailed) .000 N 399 399 SOURCES Pearson Correlation − .727 ** 1 Sig. (2-tailed) .000 N 399 399 **. Correlation is significant at the 0.01 level (2-tailed). Based on the correlation analyses of all the considered predictors of environmental awareness (demographics factors and sources of information), the average mean of the respondents awareness level of CME effects on the environment is 2.76 (2.58 + 2.71/2), an indication of low awareness. Discussion This study found that the knowledge about the effects of CME on the environment is low in the study area; with a general mean was 2.58%. Out of the fifteen raised issues, eleven indicated low awareness, while only two (Q6 & Q9) recorded a high level of awareness. About 51% of the respondents were unaware of some of the effects of CME on the environment. The percentage of the respondents who were slightly aware was 7.9%, while neutral accounted for only 0.5% as the least. Those with moderate and extreme awareness accounted for 17.3% and 23.8%. None of the respondents knows that hydrogen cyanide in cassava effluent could cause partial blindness in humans according to the study by Fajemisin et al., ( 2021 ). The sources of awareness on the effects of CME effluent on the environment in the study area are in the descending order of friends > community > TV > newspaper and internet > advertisement. The study showed a significant relationship between environmental awareness and education, occupation, and income level of residents, and the majority of the participants ended their education in a secondary school which justifies the variations and low level of awareness in the study area. Factors that informed the choice locations of cassava processing sites according to cassava factory owners (CFO) include: the availability of land, nearness to the residential area, nearness to the farm road, accessibility, proximity to a water source, and security as shown in Fig. 5 . The highest factor as indicated by the CFO is the availability of land (35%), which accounted for the reason why some built their cassava factories close to residential areas where they have landed properties either by inheritance or bought. The least considered factor was security (5%). The objectionable odor from cassava effluent remains a threat to the residents and could discourage investors from investing in the study area. This finding is in line with the study of Ehiagbonare et al. ( 2009 ), who buttressed that CME has a stinking odor that can be perceived as far as 90.3-102.3m of its source and as well causes disease. The respondents affirmed that cassava effluent is toxic, thus, should be handled with caution. The verdict corroborates the findings of Eze and Onyilide ( 2015 ). The awareness of CME to killing domestic animals like goats and sheep was glaring, as most respondents attested to it. However, during an interview with some of the cassava mill owners, it was argued that the effluent does not affect fowl but could exterminate goats and sheep. The finding is in line with the report of Ehiagbonare et al. ( 2009 ) that CME without palm oil kills domestic animals such as sheep and goats and does not affect a cat, fowl, and pigs. An interview on the purpose of red oil application to cassava during "garri" processing was conducted for some of the respondents that justified their actions based on their tradition and color only. Holistically, the essence of red oil application is to diminish the cyanogenic glucosides in cassava that is harmful to human health and the environment (Ndife et al., 2019 ; Abu et al., 2006 ). Zhu et al. ( 2015 ) added that increasing awareness of the usefulness of red palm oil in cassava as a source of vitamin A is desirable. Cassava processing effluent contains highly lethal substances that pose environmental hazards. The impact is human-induced action as cassava wastewater is discharged indiscriminately into the environment, while some are channeled into effluent ponds. Despite the channeling of the effluent into ditches from observation, the large volumes of the effluent often time overflow, join the surface runoff, and constitute a nuisance to the environment, as shown in Fig. 6. As a way of cushioning the effects of cassava effluent, particularly the odor, some of the respondents in an interview said they apply some chemicals into effluent ditches, such as “kabad” and already used torch light batteries and drilling away the cassava effluent in an already filled cemented effluent ditches into far-locations in the bush. At the time of this study, the cemented CME ditch was an innovation seen in only two locations, which should be adopted, to mitigate effluent impacts on the environment. However, leaving the effluent pond open as shown in Fig. 7 , is dicey and could induce more deaths of domestic animals, including humans, particularly children at night if not protected. Other effects of CME observed in the study area include the destruction of farmlands, nuisance, and the influx of mosquitoes in the cassava mill environment that cause malaria, the most common disease threatening the health and wellness of the residents. In this paper, awareness of the effects of CME on the environment in the study area was seen as not predicated on gender. However, the result shows a significant variation in the awareness level of CME effects on the environment with age (P = .026, F = 4.014). Other socioeconomic factors (education status, occupation, and income level) were significant. The study revealed a strong, positive correlation between environmental awareness and education, occupation, and income (concerning the effects of CME on the environment), which was statistically significant (between education and awareness, r = .808**, n = 399, p = .000; between occupation and awareness, r = .819**, n = 399, p = 0.000; and between income and awareness, r = .865**, n = 399, p = .000). Conclusion Awareness of the effects of CME on the environment was critically examined. The study concluded that awareness of the effects of CME on the environment was low in the study area. Age, education, occupation, and income were observed analytically as good predictors of environmental awareness. Cassava effluent is toxic and if discharged untreated results in environmental pollution that threatens human health and wellness, and the consequences will continue to persist if not addressed. Permeating cassava mill effluent across effluent ditches into the open field without measures to mitigate its effects indicates poor environmental awareness that worsens the aftereffects of environmental pollution. Therefore, the study recommends an awareness campaign to educate the public on the implications of cassava effluent on the environment. Overflow of CME across effluent ponds or factory walls should be prohibited. Cemented effluent ditches should be embraced, for easy treatment and management of cassava effluent before discharge. Also, the government is encouraged to give incentives to the small-scale businesses and support their production process with revenue and training for improvement of their hygiene and production sanitary standards. During interaction with the cassava mill owners, the researchers discovered that one of them controls weeds around his cassava mill site (CMS) with cassava effluents from the effluent ditch. Due to that, future research could examine the influence of cassava effluents on the production of herbicides. The study increases knowledge among the government, farmers, and the public about the environmental effects of untreated cassava mill effluents. The paper exposes to the government, environmentalists, policymakers, and the general public the problematic environment suffering from environmental pollution by cassava mill effluents and calls for prompt actions to mitigate its effects. The study creates awareness about possible measures to cushion the effects of cassava effluent on the environment, which include the new developments of channeling cassava effluents into cemented ditches for apt treatment and discharge and the zoning of cassava factory sites for effective control and management that guarantee sustainable development. It would significantly grant the researchers the privilege to make relevant contributions to areas with similar problems. It is an eye-opener for the public to realize that environmental elements do not exist in isolation, and what affects any individual species affects others as noted in ecosystem concept.. The research creates awareness that CME contributes to climate change. Furthermore, the paper creates the awareness that hydrogen cyanide in CME could cause neurological disorders, including partial blindness in humans. It also raises knowledge on the significance of applying red oil to cassava flour while processing it to reduce the toxic content of cassava cyanide in the CME. Declarations Ethical approval: The ethics committee/examination panel chaired by the dean of the Faculty of the Social sciences University of Nigeria Nuskka approved the research . Consent to Participate: The authors confirm they sought and got the consent from all participants in the study. Consent to publish: All named authors in the paper have mutually agreed that the manuscript be submitted to ESPR for publication. Author contributions: Matthew Ogorchukwu Isimah : Conceptualization, method, Analysis, Writing- Original draft. Gladys Ogochukwu Chukwurah : method, analysis, writing- secondary Francis Ogochuwku Okeke : draft, review, and validation of results, draft reviewing, and final editing. Chukwuemeka Ifedilichukwu Nnoli : Data collection, reviewing, and editing. Funding: This research did not have the courtesy of any funding from any organization. Competing interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Availability of data and materials: The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials, available at the behest of the first author. References Abu J.O, Badifu G.O, Akpapunan M.A. (2006). Effect of Crude Palm - Oil Inclusions on some Physicochemical Properties of Gari, Fermented Cassava Food Product . J. Food Sci. Technol . 24:73-79. Adeniji A.A., Ega L.A., Akoroda M.O., Adeniyi A.A., Ugwu B.O., and Balogun A. (2005). Department of Agriculture Federal Ministry of Agriculture and Natural Resources Nigeria. FAO; Cassava Development in Nigeria. Al-Rabaani A. and Al-Shuili A. (2020). Environmental Knowledge, Attitudes, and Behavior among Omani Post-Basic Education Students. European Journal of Social Sciences ISSN 1450-2267 Vol. 60 No 1 July, pp. 29-38. Ballew M., Marlon J, Leiserowitz A., and Maibach E. (2018). Gender Differences in Public Understanding of Climate Change Note · Characteristics of Soil Receiving Cassava Effluent in Elele, Rivers State, Nigeria. J Appl Environ Microbiol . 3: 20-24. Chinyere, G.C, Nwaogwugwu, C.J., Akatobi, K.U., Osuocha, K.U. (2018). Influence of Cassava Mill Effluent (CME) Dumping On Soil Physicochemical Parameters And Selected Plant Nutrientsin Uturu, Abia State Nigeria. Globalscientificjournal ( GSJ): Volume 6, Issue 1, January. Constantini E and Hanf K. 1972. Environmental Concern and Lake Tahoe: A Study of Elite Perceptions, Backgrounds and Attitudes. Environ Behav. 4:209–42. Dane, B. (2006). Likert Scales are the Meaning of life. Topic Report. CPSC681. pp. 1-10. Ehiagbonare, J. E., Enabulele, S. A., Babatunde, B. B., and Adjarhore, R. (2009). Effect of Cassava Effluents on Okada Denizens. Scientific Research and Essay, 4(4), 310 – 313. Elijah A I, Popoola O, A R and Uzochukwu S V A. (2014). Molecular Characterization and Potential of Bacterial Species Associated with Cassava Waste , Nigerian Food Journal 32(2), 56-65. Eze V. C. and Onyilide D. M.. Microbiological and Physicochemical Characteristics of Soil receiving Cassava Effluent in Elele, Rivers State, Nigeria. Journal of Applied & Environmental Microbiology . 2015; 3(1):20-24. doi: 10.12691/jaem-3-1-4 Eze, A. V. and Nwibo, S. U. (2014). Economic and Technical Efficiency of Cassava Production in Ika North East Local Government Area, of Delta State, Nigeria. Journal of Development and Agricultural Economics . Vol. 6(10), pp. 429-436, DOI: 10.5897 /JDAE2013.0541. Ezeigbo O R, Ike-Amadi, C A Okeke U P, Ekaoko M U (2014). The Effect of Cassava Mill Effluent on Soil Microorganisms in Aba, Nigeria , International Journal of Current Research in Bioscience and Plant Biology 1(4), pp21-26. Fajemisin E., Ogungbemi S. E. and Tunde A. A. (2021). Partially-Processed Cassava Tubers on Poor Eye Vision in Nigeria: Impacts and Solutions. FAO and IFAD, (2001). Strategic Environmental Assessment: An Assessment of the Impact of Cassava Production and Processing on the Environment and Biodiversity. Proceedings of the Validation Forum on the Global Development Strategy, April 10-12, Rome, Italy. Izah S.C, Bassey S.E, Ohimain E.I (2017). Assessment of Heavy Metal in Cassava Mill Effluent Contaminated Soil in a Rural Community in the Niger Delta Region of Nigeria. EC Pharmacology and Toxicology 4(5): 186-201.21. Izah S.C, Bassey S.E, Ohimain E.I (2017). Cyanide and Macro-nutrients Content of Saccharomyces Cerevisiae Biomass Cultured in Cassava Mill Effluents. International Journal of Microbiology and Biotechnology 2(4): 176-180.24. Izah S.C, Bassey S.E, Ohimain E.I (2017). Geo-accumulation Index, Enrichment Factor and Quantification of Contamination of Heavy Metals in Soil Receiving Cassava Mill Effluents in a Rural Community in the Niger Delta Region of Nigeria. Molecular Soil Biology 8(2): pp7-20. Izah SC, Bassey SE, Ohimain El. (2017) Removal of heavy metals in cassava mill effluents by saccharomyces cerevisiaeisolated from palm wine. MOJ Toxicol.;3(4):83–87. DOI: 10.15406/mojt.2017.03.00058 Izah S.C, Bassey S.E, Ohimain E.I (2018). Ecological Risk Assessment of Heavy Metals in Cassava Mill Effluents Contaminated Soil in a Rural Community in the Niger Delta Region of Nigeria. Molecular Soil Biology. Izah S.C, Bassey S.E, Ohimain EI (2018). Impacts of Cassava Mill Effluents in Nigeria. Journal of Plant and Animal Ecology 1(1): 14-42.2. Izah S.C, Bassey SE, Ohimain E.I (2017). Assessment of some Selected Heavy Metals in Saccharomyces Cerevisiae Biomass Produced from Cassava Mill Effluents. EC Microbiology 12(5): 213-223.23. Martínez-Borreguero G., Maestre-Jimenez J., Mateos-Núñez M., and Naranjo-Correa F.L (2020). Analysis of Environmental Awareness, Emotions and Level of Self-Efficacy of Teachers in Training within the Framework of Waste for the Achievement of Sustainable Development. Sustainability . DOI: 10.3390/su12062563. Ndife J., Nwaubani O. and Aniekpeno I. E. (2019). Effect of Palm Oil Inclusion on the Quality of Garri Produced from White and Yellow Cassava ( Manihot esculenta cranz ) Roots. International Journal of Food Science and Nutrition . Volume 4; Issue 3; May 2019; pp180-185. ISSN: 2455-4898 Nwaugo V.O., Chima G.N., Etok C.A. and Ogbonna C.E. 2008. Impact of Cassava Mill Effluent (CME) on Soil Physicochemical and Microbial Community Structure and Functions. Nig J Microbiol., 22: 1681-1688. Nwokoro, O., Anya, F. O., and Eze, I. C. (2013). The Use of Microorganisms in Increasing the Protein Yield of Cassava (Manihot esculenta Crantz) Peel Wastes. Polish Journal of Chemical Technology, 15(2), 112 – 115. Obueh H.O, Odesiri-Eruteyan E. (2016). A Study on the Effects of Cassava Processing Wastes on the Soil Environment of a Local Cassava Mill. J Pollut Eff Cont 4: 177. doi: 10.4176/2375-4397.1000177. Odoabuchi, V.E., Ejiogu, C.C., Nwanya, E., and Azubuike, C. (2020). Effect of Cassava Mill Effluent on Microbial Properties of Garden Soil: Eziobodo Imo State NIGERIA. International Journal of Environment and Pollution Research Vol.8, No.3, pp.1-17. Oghenejoboh1 K. M. (2015). Effects of Cassava Wastewater on the Quality of Receiving Water Body Intended for Fish Farming. 6(2): 164-171, Article no.BJAST.2015.077 ISSN: 2231-0843. Ohimain E.I, Izah S.C. (2017). A Review of Biogas Production from Palm Oil Mill Effluents using Different Configurations of Bio Reactors. Renewable and Sustainable Energy Reviews Volume 70, Pages 242-253 Okechi R.N , Chukwura, E.I , Azuwike CO, and Ihejirika C.E. (2011). The impact of cassava mill effluent on the total aerobic bioload and Physicochemical Properties of the Soil. Journal of Biodiversity and Environmental Sciences (JBES) , Vol. 1, No. 6, p. 112-117. ISSN: 2220-6663. Okeke, F. O., Eziyi, I. O., Udeh, C. A., & Ezema, E.C. (2020) City as Habitat: Assembling the fragile city. Civil engineering Journal 2020; 6(6):1143-1154. doi: http://dx.doi.org/10.28991/ cej-2020-03091536 Omomowo I O., et al. (2015). “Bacteriological Screening and Pathogenic Potential of Soil Receiving Cassava Mill Effluents”. International Journal of Basic and Applied Science 3.4 pp26-36. Rauwald K.S and Moore C.F. (2002). Environmental Attitudes as Predictors of Policy Support Across Three Countries. Environ Behav. 34:703–9 Rilwani, M.L. (2005). Statistics for Environmental and Social Sciences 11.Esa-way Computers 22-43. Sakellari M. and Skanavis C, (2013). Environmental Behaviour and Gender: An Emerging Area of Concern for Environmental Education Research. Journal of Applied Environmental Education & Communication. Volume 12, The Nation Newspaper (2018). Eight deadliest diseases in Nigeria. Sept. 19 th . Ugbomeh B. A. (2011). Household Size and Socio-economic Resource. A Case study of Ika North East L. G.A. Delta State Nigeria. An International Multi-Disciplinary Journal , Ethiopia Vol. 5 (1), Pp226-238. Serial No. 18, January, Ustun B. and Celep B. (2007). The Connection between Environmental Awareness and Socio-Economic and Cultural structure. WIT Transactions On Ecology and the Environment, Vol 102, WIT Press Sustainable Development and Planning III 623. doi:10.2495/SDP070602. Yamane, T. (1967). Statistics . An Introductory Analysis, 2nd Edition, New York, Happer and Row. Zhu C., Cai Y., Gertz E. R., La Frano M. R Dustin J., Burnett D.J., and Burri B.J. (2015). Red Palm Oil-supplemented and Bio-fortified Cassava Gari Increase the Carotenoid and Retinyl Palmitate Concentrations of Triacylglycerol-rich Plasma in Women. Nutr. Res. Nov; 35(11): pp965–974. Ziadat, A.H. (2010) Major factors contributing to environmental awareness among people in a third world country/Jordan. Environ Dev Sustain 12, 135–145 https://doi.org/10.1007/s10668-009-9185-4 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6968127","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":475904723,"identity":"b8994ad0-6e3e-4c4c-b4b4-88d93617b521","order_by":0,"name":"Matthew Ogorchukwu Isimah","email":"","orcid":"","institution":"University of Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"Ogorchukwu","lastName":"Isimah","suffix":""},{"id":475904954,"identity":"0a239de5-cb04-4bff-81bb-3fb553f7288a","order_by":1,"name":"Gladys Ogochukwu Chukwurah","email":"data:image/png;base64,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","orcid":"","institution":"University of Nigeria","correspondingAuthor":true,"prefix":"","firstName":"Gladys","middleName":"Ogochukwu","lastName":"Chukwurah","suffix":""},{"id":475904992,"identity":"45eaab50-345b-4c91-b3d8-b1438d52dae2","order_by":2,"name":"Francis Ogochukwu Okeke","email":"","orcid":"","institution":"Canterbury Christ Church University","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"Ogochukwu","lastName":"Okeke","suffix":""},{"id":475905101,"identity":"c625d1f2-3505-41d2-b4a5-d4d31a5ccce9","order_by":3,"name":"Cletus Famous Nwankwo","email":"","orcid":"https://orcid.org/0000-0003-0071-4903","institution":"University of Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Cletus","middleName":"Famous","lastName":"Nwankwo","suffix":""},{"id":475905154,"identity":"f1d3540e-1531-45a7-ad08-364504b55927","order_by":4,"name":"Chukwuemeka Ifedilichukwu Nnoli","email":"","orcid":"","institution":"University of Nigeria","correspondingAuthor":false,"prefix":"","firstName":"Chukwuemeka","middleName":"Ifedilichukwu","lastName":"Nnoli","suffix":""}],"badges":[],"createdAt":"2025-06-24 17:42:17","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6968127/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6968127/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85396089,"identity":"0332a048-a191-4ee7-8fa3-3339c113f4b7","added_by":"auto","created_at":"2025-06-25 11:10:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":276231,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3\u003c/strong\u003e:\u003csup\u003e\u0026nbsp; \u003c/sup\u003eIka\u003csup\u003e \u003c/sup\u003eNorth East\u003csup\u003e \u003c/sup\u003eL. G. A. Showing the Study\u003csup\u003e \u003c/sup\u003eArea\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u003c/strong\u003e GIS Lab. Department of Geography UNN, 2022\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/3587271c42dc28857cc1a981.png"},{"id":85396545,"identity":"008cdb09-0bf6-427d-8b0e-d487dd665352","added_by":"auto","created_at":"2025-06-25 11:18:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1821372,"visible":true,"origin":"","legend":"\u003cp\u003eCassava Mill Site\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/21b6e5843ca2cae2ec7bc3b6.png"},{"id":85396095,"identity":"9322e27a-1889-48a7-b5cf-79c02728bef8","added_by":"auto","created_at":"2025-06-25 11:10:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1275966,"visible":true,"origin":"","legend":"\u003cp\u003eCassava Dewatering Site\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/460f7d8b7bd678199027e01a.png"},{"id":85396090,"identity":"b62036dd-611f-47dd-81de-2a277a648096","added_by":"auto","created_at":"2025-06-25 11:10:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":26788,"visible":true,"origin":"","legend":"\u003cp\u003eSources of Awareness on the Environmental Effects of Cassava Mill Effluent\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/f84293172e30519940945187.png"},{"id":85396546,"identity":"950052f2-bf13-4ccd-aaa5-6eca94d2ba3e","added_by":"auto","created_at":"2025-06-25 11:18:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13850,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/792de61bb2064c6b4cd90d39.png"},{"id":85396097,"identity":"3d125af9-18f1-4a71-b083-2c1d6f3775d4","added_by":"auto","created_at":"2025-06-25 11:10:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":185733,"visible":true,"origin":"","legend":"\u003cp\u003eOverflow of CME Across Mill Pond.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u003c/strong\u003e Author’s Fieldwork, 2022.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/687834ae2fc133dd9b1d5979.png"},{"id":85396099,"identity":"1dd4b8ab-a8ed-446f-92bc-43cf99fdd1c8","added_by":"auto","created_at":"2025-06-25 11:10:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":453687,"visible":true,"origin":"","legend":"\u003cp\u003eCemented CME Ditch in the Study Area\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/6d3c9ed32c14df1709b6c24e.png"},{"id":85398599,"identity":"c1745ad4-fd36-4153-9e70-05861054df7d","added_by":"auto","created_at":"2025-06-25 11:34:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5840228,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6968127/v1/afb3553a-2025-4c79-833e-e41dafd4cb56.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAwareness of the effects of Small-Scale Cassava Mill Effluent on the Environment in Ika North East Local Government Area, Delta State, Nigeria\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMost third world economies are experiencing increased human population and Nigeria\u0026rsquo;s demographic change has been drastic (Okeke et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). With her fast-growing human population, the need for more food production is indispensable (Okeke et al., 2023). Cassava (Manihot esculenta) is a major staple food produced in the developing world, supplying food for over 500\u0026nbsp;billion people (Odoabuchi et al, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Nwokoro et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Abu et al, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). It was first cultivated in South America and introduced to Nigeria in the sixteenth century (Adeniji et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Cassava is a perennial woody shrub, grown as an annual crop and serves as a cheap and rich source of carbohydrates, protein and vitamins A, B, and C when the leaves of the cassava are eaten as green vegetables (Eze and Nwibo, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Omomowo et. al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Currently, the global production of cassava is about 215, 436, 496 out of these, Nigeria accounts for 20.6% being the largest producing nation (Izah et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Izeh et al, 2018; Obueh and Odesiri-Eruteyan, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe significance of cassava production in Nigeria in terms of food, employment, and source of income to farmers and the nation at large is not in doubt (Izah et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, the attendant effects of cassava mill effluent (CME) on the environment are challenging (Cumbana et al, 2007). Cassava effluent contains a high contaminating load of biological oxygen demand (BOD) and high cyanide content (Okunade and Adakalu, 2012) that can induce toxicological effects on the environments and its biotas such as humans, fisheries, flora, and fauna (Izah et al, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Consequently, the CME discharge into the soil untreated prevents germination, inhibits plant growth, reduces plant yield, contaminates water bodies, and produces an offensive odor that disturbs the comfort of the populace (Izah et al, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nwaugo et al, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Izah and Seiyaboh, 2018; Ezeigbo et al, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Besides, Cassava wastewater ponds serve as a breeding point for mosquitoes that causes malaria, the commonest disease threatening lives in Africa where thirty countries in Sub-Saharan Africa account for 90% of global malaria deaths (The Nation Newspaper, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe threat of environmental pollution in Nigeria particularly in Delta state is not only attributed to oil spills but as well as the discharge of cassava mill effluent which oftentimes is disposed indiscriminately. The boom of Cassava for multiple uses has attracted a lot of small-scale cassava processing factories sited around residential areas in Nigeria (Okechi et al, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), producing a large volume of cassava effluent with little or no attention to environmental pollution (Elijah et al, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nwaugo, 2008; Izah, 2018). Most millers that process and manage cassava mill industries do not have adequate knowledge of environmental safety, and the indiscriminate discharge of cassava effluent by farmers at the milling sites also suggests their slim understanding of the implications (Oghenejoboh, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, many researchers have studied the impact of cassava mill effluent on the environment in Nigeria. For instance, Obueh and Odesiri-Eruteyanm (2016) studied the \u0026ldquo;Effects of Cassava Processing Wastes on the Soil Environment of a local cassava mill in Ekiadolor, Ovia North East Local Government Area of Edo State, Nigeria\u0026rdquo;. Their findings showed that the continuous disposal of the cassava processing wastes in the soil environment around the mill and into a waste pit reduces soil quality and renders the environment polluted. Izah, et al (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) researched the Impact of Cassava Milling Effluent in Nigeria and found that CME alters the quality of soil and water with regard to physicochemical, heavy metal, and microbial characteristics. Similarly, Chinyere et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) studied on Influence of Cassava Mill Effluent (CME) Dumping on Soil Physicochemical Parameters and Selected Plant Nutrients in Uturu, Abia State, Nigeria. Their findings showed that excess soil moisture of the CME-impacted soil is capable of limiting soil oxygen available to plants and thus alters microbial activities. But no study has focused on awareness of the effects of cassava effluent on the environment and no research on cassava effluent has been done in the study area. Consequent on these, being environmentally unaware could worsen the effects of CME on the environment. Hence, the need to investigate the demographic status, level and sources of environmental awareness of people on the effects of CME on the environment, and the factors influencing the choice locations of cassava processing sites to bridge the study gap.\u003c/p\u003e \u003cp\u003eZiadat (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) opined that to better understand environmental attitudes, the level of knowledge possessed by the population under observation concerning the severity of environmental problems, and their reaction to and their interactions with nature must be ascertained by assessing environmental awareness. This has long been recognized in the more industrialized and developed nations of the world where many studies of environmental knowledge have been conducted over the last three decades (Constantini and Hanf \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Rauwald and Moore \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). With this background, this study aimed at examining Awareness of the Effects of Small-Scale Cassava Mill Effluent on the Environment of Ika North East Local Government Area, Delta State, Nigeria, with the objectives of determining the demographic characteristics of the respondents, the level of awareness of the effects of CME on the environment in the study area, sources of awareness, factors that informed millers\u0026rsquo; choice location of cassava processing site, and perceived effects of CME on the environment.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHypotheses\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is no significant difference between male and female gender in awareness of the effects of CME on the environment among residents in the study area.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is no significant variation in the awareness of the effects of CME on environments in relation to age.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is no significant relationship between the awareness of the effects of CME on the environment and the socioeconomic status of residents in the study area.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThere is no significant relationship between awareness and sources of information about the effects of CME on the environment.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003e2.1 The Study Area\u003c/h3\u003e\n\u003cp\u003eIka North-East Local Government Area lies between Latitude 6\u003csup\u003e0\u003c/sup\u003e 07\u003csup\u003e1\u003c/sup\u003e 47\u003csup\u003e11\u003c/sup\u003e and 6\u003csup\u003e0\u003c/sup\u003e 19\u003csup\u003e1\u003c/sup\u003e 07\u003csup\u003e11\u003c/sup\u003e N of the equator and between Longitude 6\u003csup\u003e0\u003c/sup\u003e 10\u003csup\u003e1\u003c/sup\u003e 25\u003csup\u003e11\u003c/sup\u003e and 6\u003csup\u003e0\u003c/sup\u003e 22\u003csup\u003e1\u003c/sup\u003e 37\u003csup\u003e11\u003c/sup\u003e E of the Greenwich meridian. It is bounded in the North by Edo State and Ika South Local Government Area. However, Ika South Local Government Area marks its Southern and Western limits, while Aniocha North and Aniocha South Local Government Areas marked its Eastern margin (Ugbomeh, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Ika North East Local Government Area of Delta State occupies an area of about 463 km\u0026sup2; with a population figure of 126,560 in 1991 with 61,303 males and 65,255 females (Eze and Nwibo, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; NPC, 2006, cited in Ugbomeh, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The projected population of the area for 2022 is 272283. There are nine communities made up of Ika North East Local Government Area which include; Owa, Ute-Ogbeje, Ute-Okpu, Akumazi, Umunede, Idumuesah, Igbodo, Otolokpo and Mbiri (Eze and Nwibo, 2013) that spread out into fourteen wards in the area (Eze and Nwibo, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The locations of these communities are indicated in the map of the study area as shown in Fig.\u0026nbsp;1.\u003c/p\u003e\u003cp\u003eGenerally, the terrain of Ika North East Local Government Area is characterized by undulating lowlands. The soils are sandy and loamy and are rich for agriculture and socio-economic activities. The environment has natural vegetation and water resources that support agricultural activities. The main occupation of the people is farming with cassava being the highest food crop produced and a major source of livelihood for the residents. The people are well known for \u0026ldquo;garri\u0026rdquo; production (cassava flakes) as shown in Figs. 1 \u0026amp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis study employed both primary and secondary data to elicit relevant information. Primary data were sourced through structured questionnaires, informal interviews, and personal observation in a small-scale cassava processing environment. A total of 399 questionnaires were administered to the respondents using systematic random sampling. The sample size was obtained from the 2022 projected population of the study area with the formula: n\u0026thinsp;=\u0026thinsp;N/{1+ (e)\u003csup\u003e2\u003c/sup\u003e }. Where: n\u0026thinsp;=\u0026thinsp;total sample size, N\u0026thinsp;=\u0026thinsp;total population of the study area, e\u0026thinsp;=\u0026thinsp;level of precision (0.05), and 1\u0026thinsp;=\u0026thinsp;unity (a constant) (Yamane, 1969). The questionnaire comprised two sections: a demographic section (gender, age, marital status, education, and occupation) and section two with fourteen questions about awareness of environmental pollution by CME. The questionnaires were administered within the nine communities that made up the study area according to their sample sizes as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The sample size of each community was calculated with the formula: total sample size of the study area multiplied by the population of each community, divided by the population of the entire study area (Rilwani, \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e). The researchers employed the services of four indigenes for questionnaire administration. To ascertain the level of awareness of the effects of CME on the environment, respondents were told to tick appropriately the scaling of the awareness based on five Likert Scale items (1\u0026thinsp;=\u0026thinsp;not aware, 2\u0026thinsp;=\u0026thinsp;slightly aware, 3\u0026thinsp;=\u0026thinsp;neutral, 4\u0026thinsp;=\u0026thinsp;moderately aware, and 5\u0026thinsp;=\u0026thinsp;extremely aware). The Likert scale is a non-comparative scaling technique and psychometric response scale which is used in surveys for the reason of obtaining the degree of agreement of respondents with a set of statements (Dane \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). Interviews were conducted with ten owners/operators of cassava processing engines and nineteen 19 persons among the respondents to express their experiences and opinion regarding the effects of cassava effluents on the environment. Secondary data were obtained from journals, newspapers, textbooks, and other internet materials. The projected population of the study area for 2022 is 272283 using the extrapolation method p\u003csup\u003en\u003c/sup\u003e= p\u003csup\u003eo\u003c/sup\u003e(1\u0026thinsp;+\u0026thinsp;r)\u003csup\u003en\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eWhere p\u003csup\u003en\u003c/sup\u003e= present population,\u003c/p\u003e\n\u003cp\u003ep\u003csup\u003eo\u003c/sup\u003e = target population,\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;number of year(s) for the last population and\u003c/p\u003e\n\u003cp\u003er\u0026thinsp;=\u0026thinsp;growth rate (Yamane, \u003cspan class=\"CitationRef\"\u003e1967\u003c/span\u003e; Rilwani, \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor this study, a 2.5% growth rate was used.\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePopulation and Sample Sizes of Each Community in the Study Area.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCommunity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1991 Census\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2006 Projected\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022 Projected\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSample Size\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOwa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMbiri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIgbodo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUmunede\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAkumazi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIdumuesah\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOtolokpo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUte-ogbeje\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUte-okpu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e126560\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e183416\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e272283\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e399\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eThe study used descriptive and inferential statistics to analyze the collected data through SPSS version 21.0. The descriptive analysis includes frequency tables, percentages, and charts. On the other hand, Student T-test, ANOVA, and Pearson\u0026rsquo;s Correlation were adopted to analyze the three stated hypotheses. The techniques are appropriate for this study as they checkmate the significant differences and relationships between two or more independent variables.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cimg 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\"\u003e\u003c/div\u003e\n\u003c/div\u003e\n"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDemographic Characteristics of the Respondents\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the demographic characteristics of the sampled population of the study.\u003c/p\u003e \u003cp\u003eOut of 399 sampled respondents, 27.6% of the respondents are male; while 72.4% are female which indicates that female was more involved among the participants. The findings show that 5.0% of the respondents are less than 18 years of age, while 42.4% of the respondents are between the age of 18\u0026ndash;33 years. The majority of the respondents (45.1%) were between the age of 34 years to 49 years, and 7.5% of the respondents are aged 50 and above. Age is vital in any population as it determines the working force that contributes maximally to the socio-economic life of people. In terms of education, 19.3 percent of the respondents attended primary school, 70.1% secondary, and 10.1% tertiary institutions. The implication is that buck of the respondents who were equally farmers stopped their education in secondary school probably due to financial constraints as some voiced out during an interview. There was no record of unschooled. The highest percentages (75.1%) of the participants are farmers who solely rely on the income from the farm for their livelihood. The students (12.5%) who participated were second to the highest in terms of occupation. The business accounted for 7.5% of the respondents as against 4.8% of the civil servants who participated. None of the respondents indicated unschooled. The highest percentages (62.7%) of the respondents earn #20,000-#40,000 per month, followed by 24.1% of those who earn less than #20,000 per month. The next is 10.8% of those whose monthly take home was #61,000, while 2.5% of the respondents realized #41,000-#60,000 per month\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Respondents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 18 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;33 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 years and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCivil Servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; #20,000 per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e#20,000- #40,000 per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e#41,000 - #60,000 per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e#61, 000 and above per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAwareness of the Effects of CME on the Environment\u003c/h3\u003e\n\u003cp\u003eThe general knowledge of 399 respondents on the effects of cassava mill effluent on the environment was explored as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Though the effects of CME on the environment are not new to the respondents, the majority of the participants do not have adequate knowledge of its attendant effects. Results revealed 51.3% of the respondents indicated not being aware of some effects of CME on the environment in terms of land degradation, water contamination, and air pollution. About 0.5% of the participants were neutral (neither aware nor not aware). However, 7.5% of respondents have slight awareness, followed by 17.3% of the participant with moderate awareness, and 23.8% were extremely aware. From the data obtained, except questions 6 \u0026amp; 9 which recorded a high level of awareness, and questions 10 \u0026amp; 7 which indicated moderate awareness, all other ones were low. Having a general mean of 2.58 is an indication of low awareness of the effects of CME on the environment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResult Responds to All Questionnaires.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQuestion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Number Answered\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eSentiment Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRemark\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Aware %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlightly Aware %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNeutral %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerately Aware %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eExtremely Aware %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e51.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e17.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e23.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e38.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrand Mean\u0026thinsp;=\u003c/b\u003e\u0026thinsp;38.1/15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eLow\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eSources of Awareness on the Effects of CME on Environmental\u003c/h3\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e constitutes the respondent\u0026rsquo;s sources of information on environmental pollution occasioned by CME in the study area. The finding shows that 3% of the respondents obtained knowledge of environmental pollution by CME from newspapers. Those who got information from TV are 9%, followed by 3% from the internet, 49% from friends, 35% from the community, and 1% from advertisements. It implies that buck of the knowledge on environmental pollution caused by CME in the study area, came from friends probably at the grating site where the effects are felt mostly, particularly the offensive odor. The implication is that the extent of awareness from a friend is predicated on the level of exposure of the person.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFactors that Informed Miller's Choice Location of Cassava Processing Plants\u003c/h2\u003e \u003cp\u003eFig. 5 shows the various factors that informed the miller\u0026rsquo;s choice of location of cassava processing machines in the study area. The highest factor as indicated by 35% of the respondents was the availability of land, followed by nearness to residential location as 19% of the respondents claimed. The respondents who choose nearness to farm road as a major factor are 18%. Other respondents who considered accessibility, proximity to a water source, and security were 17%, 6.0%, and 5.0% respectively. The study shows that factory owners did not consider the effects of CME on the environment before building their industry. None of the respondents considered government policy as a factor.\u0026nbsp;\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEnvironmental Awareness and Socio-economic Factors\u003c/h3\u003e\n\u003cp\u003eEnvironmental concern is influenced by socioeconomic status. Oftentimes, those with high environmental awareness, have much concern for their environment, which is linked to several factors like educational background. Those with low socioeconomic levels think more about satisfying their immediate material needs than environmental issues. As such, considering socioeconomic factors is assumed essential in assessing the environmental awareness of any society. The awareness levels of the participants based on their socioeconomic status are presented in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAwareness Responds Based on Socioeconomic Factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot Aware\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSlightly Aware\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModerately\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eExtremely Aware\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 18 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;33 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 yrs \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCivil Servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; #20,000 per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e#20,000- #40,000 per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e#41,000 - #60 ,000 per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e#61, 000 and above per month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eGender\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the level of awareness based on the respondents\u0026rsquo; socioeconomic status. The male awareness follows in the order of 14 persons that are extremely aware, 41 moderately aware, 5 neutral, 40 slightly aware and 10 not aware. The awareness of females is in the order of 25 extremely aware, 109 moderately aware, 10 neutral, 120 slightly aware, and 25 not aware. To obtain more objective measures, the influence of gender on environmental awareness was determined, using a student t-test. The result revealed no significant difference between male and female gender in awareness of the effects of CME on the environment as the P-value is greater than a 95% level of confidence(t\u0026thinsp;=\u0026thinsp;2.267, df\u0026thinsp;=\u0026thinsp;4, n\u0026thinsp;=\u0026thinsp;399. P\u0026thinsp;=\u0026thinsp;.086). The null hypothesis indicated in hypothesis 4 was rejected, while the alternative was accepted. It implies that gender is insignificant for the prediction of awareness level of the effects of CME on the environment in the study area. To some scholars, men are more active in education and social lives for a long time, as such, should be more concerned and knowledgeable about the immediate environment. But due to the quest to make more money to meet up his social responsibilities, ponder less on environmental issues (Ustun and B. Celep, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Ballew et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) argued that average women are slightly more likely than men to be concerned about the environment and have stronger pro-climate opinions and beliefs.\u003c/p\u003e \u003cp\u003eHowever, the result of this study showed no significant difference which contradicts the assertion of some scholars who posit a disparity between male and female gender in environmental knowledge (Al-Rabaani and Al-Shuili, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mart\u0026iacute;nez-Borreguero et al, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, an inferential analysis was carried out based on the age of the participants. The idea was to examine whether age could influence awareness of environmental pollution via cassava effluent. The ANOVA result shows that there is a significant difference in the level of awareness of the effects of CME on the environment in relation to age (P\u0026thinsp;=\u0026thinsp;.026, F\u0026thinsp;=\u0026thinsp;4.014) at a 95% level of significance. This implies that age plays a significant role in the prediction of environmental awareness about cassava effluent pollution. Pearson\u0026rsquo;s product-moment coefficient was run to examine the relationship between awareness and socioeconomic status of respondents in terms of the effects of CME on the environment. The factors considered for the analysis are education, occupation, and income. The variables in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e were used to examine the correlation. The results revealed a strong, positive correlation between environmental awareness and education/occupation/income (concerning the effects of CME on the environment) as stated in hypothesis 3, which were statistically significant (Between education and awareness, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.808\u003csup\u003e**\u003c/sup\u003e, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;399, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.000; occupation and awareness, r\u0026thinsp;=\u0026thinsp;.819\u003csup\u003e**\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;399, p\u0026thinsp;=\u0026thinsp;.000; income and awareness, r\u0026thinsp;=\u0026thinsp;.865\u003csup\u003e**\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;399, p\u0026thinsp;=\u0026thinsp;.000). The summary of the result is in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Pearson Correlations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEDUCATION\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOCCUPATION\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eINCOME\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAWARENESS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEDUCATION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.735\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.891\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.808\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eOCCUPATION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.735\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.812\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.819\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eINCOME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.891\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.812\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.865\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAWARENESS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.808\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.819\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.865\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between Environmental Awareness and Source of Information\u003c/h2\u003e \u003cp\u003eThe pursuit of environmental sustainability is commendable, considering the rate of abuse of the natural resources in our environment. However, it requires continued environmental education to change the perceptions and attitudes of people towards the environment around us for sustainable development. The likelihood of obtaining adequate and reliable information depends on the sources of such information and the exposure of the disseminator. Udalov et al. (2021) opine that \"different information sources might have different effects on environmental concern\"; as a result, the study examines the relationship between awareness and sources of information about the effects of CME on the environment. Among the selected sources of environmental awareness, only the internet source recorded a moderate level, while the rest were low, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLevel of Awareness on the Effects of CME on the Environment and Sources of the Information\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSource of Awareness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of Response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eSentiment Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRemark\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNot Aware\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlightly Aware\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModerately Aware\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eExtremely Aware\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eResponse.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNewspaper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95/36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriends\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e453/195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e336/140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.53/6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTest of Hypothesis\u003c/h2\u003e \u003cp\u003eThe Pearson correlation result showed a significant relationship between environmental awareness and source of information (r = -659, P-value\u0026thinsp;=\u0026thinsp;0.0000), as presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Since the P-value is significant at 0.01 confidence level, the null hypothesis, as stated in Hypothesis 4, was accepted. The significance is positive and strong. Therefore, the source of information should be considered a predictor in addressing environmental awareness. The result implies that, all things being equal, increases in the quality and reliability of information sources could increase people's knowledge of CME effects on the environment. In other words, the level of environmental awareness depends on sources of information. One would ordinarily expect that since the number of respondents from friends and the community is high, their awareness should have increased. However, the source of information determines public perceptions of the environment and the value of that information, which helps in shaping people's behaviours towards the environment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Pearson Product Moment Correlation showing Relationship between Source of Information and Respondents\u0026rsquo; Level of Awareness of the Effects of CME on the Environment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAWARENESS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSOURCES\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAWARENESS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.727\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSOURCES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.727\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the correlation analyses of all the considered predictors of environmental awareness (demographics factors and sources of information), the average mean of the respondents awareness level of CME effects on the environment is 2.76 (2.58\u0026thinsp;+\u0026thinsp;2.71/2), an indication of low awareness.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study found that the knowledge about the effects of CME on the environment is low in the study area; with a general mean was 2.58%. Out of the fifteen raised issues, eleven indicated low awareness, while only two (Q6 \u0026amp; Q9) recorded a high level of awareness. About 51% of the respondents were unaware of some of the effects of CME on the environment. The percentage of the respondents who were slightly aware was 7.9%, while neutral accounted for only 0.5% as the least. Those with moderate and extreme awareness accounted for 17.3% and 23.8%. None of the respondents knows that hydrogen cyanide in cassava effluent could cause partial blindness in humans according to the study by Fajemisin et al., (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). The sources of awareness on the effects of CME effluent on the environment in the study area are in the descending order of friends\u0026thinsp;\u0026gt;\u0026thinsp;community\u0026thinsp;\u0026gt;\u0026thinsp;TV\u0026thinsp;\u0026gt;\u0026thinsp;newspaper and internet\u0026thinsp;\u0026gt;\u0026thinsp;advertisement. The study showed a significant relationship between environmental awareness and education, occupation, and income level of residents, and the majority of the participants ended their education in a secondary school which justifies the variations and low level of awareness in the study area. Factors that informed the choice locations of cassava processing sites according to cassava factory owners (CFO) include: the availability of land, nearness to the residential area, nearness to the farm road, accessibility, proximity to a water source, and security as shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. The highest factor as indicated by the CFO is the availability of land (35%), which accounted for the reason why some built their cassava factories close to residential areas where they have landed properties either by inheritance or bought. The least considered factor was security (5%).\u003c/p\u003e\n\u003cp\u003eThe objectionable odor from cassava effluent remains a threat to the residents and could discourage investors from investing in the study area. This finding is in line with the study of Ehiagbonare et al. (\u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e), who buttressed that CME has a stinking odor that can be perceived as far as 90.3-102.3m of its source and as well causes disease. The respondents affirmed that cassava effluent is toxic, thus, should be handled with caution. The verdict corroborates the findings of Eze and Onyilide (\u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). The awareness of CME to killing domestic animals like goats and sheep was glaring, as most respondents attested to it. However, during an interview with some of the cassava mill owners, it was argued that the effluent does not affect fowl but could exterminate goats and sheep. The finding is in line with the report of Ehiagbonare et al. (\u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e) that CME without palm oil kills domestic animals such as sheep and goats and does not affect a cat, fowl, and pigs. An interview on the purpose of red oil application to cassava during \u0026quot;garri\u0026quot; processing was conducted for some of the respondents that justified their actions based on their tradition and color only. Holistically, the essence of red oil application is to diminish the cyanogenic glucosides in cassava that is harmful to human health and the environment (Ndife et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Abu et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). Zhu et al. (\u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) added that increasing awareness of the usefulness of red palm oil in cassava as a source of vitamin A is desirable. Cassava processing effluent contains highly lethal substances that pose environmental hazards. The impact is human-induced action as cassava wastewater is discharged indiscriminately into the environment, while some are channeled into effluent ponds. Despite the channeling of the effluent into ditches from observation, the large volumes of the effluent often time overflow, join the surface runoff, and constitute a nuisance to the environment, as shown in Fig. 6.\u003c/p\u003e\n\u003cp\u003eAs a way of cushioning the effects of cassava effluent, particularly the odor, some of the respondents in an interview said they apply some chemicals into effluent ditches, such as \u0026ldquo;kabad\u0026rdquo; and already used torch light batteries and drilling away the cassava effluent in an already filled cemented effluent ditches into far-locations in the bush. At the time of this study, the cemented CME ditch was an innovation seen in only two locations, which should be adopted, to mitigate effluent impacts on the environment. However, leaving the effluent pond open as shown in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, is dicey and could induce more deaths of domestic animals, including humans, particularly children at night if not protected.\u003c/p\u003e\n\u003cp\u003eOther effects of CME observed in the study area include the destruction of farmlands, nuisance, and the influx of mosquitoes in the cassava mill environment that cause malaria, the most common disease threatening the health and wellness of the residents. In this paper, awareness of the effects of CME on the environment in the study area was seen as not predicated on gender. However, the result shows a significant variation in the awareness level of CME effects on the environment with age (P\u0026thinsp;=\u0026thinsp;.026, F\u0026thinsp;=\u0026thinsp;4.014). Other socioeconomic factors (education status, occupation, and income level) were significant. The study revealed a strong, positive correlation between environmental awareness and education, occupation, and income (concerning the effects of CME on the environment), which was statistically significant (between education and awareness, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.808**, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;399, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.000; between occupation and awareness, r\u0026thinsp;=\u0026thinsp;.819**, n\u0026thinsp;=\u0026thinsp;399, p\u0026thinsp;=\u0026thinsp;0.000; and between income and awareness, r\u0026thinsp;=\u0026thinsp;.865**, n\u0026thinsp;=\u0026thinsp;399, p\u0026thinsp;=\u0026thinsp;.000).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAwareness of the effects of CME on the environment was critically examined. The study concluded that awareness of the effects of CME on the environment was low in the study area. Age, education, occupation, and income were observed analytically as good predictors of environmental awareness. Cassava effluent is toxic and if discharged untreated results in environmental pollution that threatens human health and wellness, and the consequences will continue to persist if not addressed. Permeating cassava mill effluent across effluent ditches into the open field without measures to mitigate its effects indicates poor environmental awareness that worsens the aftereffects of environmental pollution. Therefore, the study recommends an awareness campaign to educate the public on the implications of cassava effluent on the environment. Overflow of CME across effluent ponds or factory walls should be prohibited. Cemented effluent ditches should be embraced, for easy treatment and management of cassava effluent before discharge. Also, the government is encouraged to give incentives to the small-scale businesses and support their production process with revenue and training for improvement of their hygiene and production sanitary standards. During interaction with the cassava mill owners, the researchers discovered that one of them controls weeds around his cassava mill site (CMS) with cassava effluents from the effluent ditch. Due to that, future research could examine the influence of cassava effluents on the production of herbicides.\u003c/p\u003e \u003cp\u003eThe study increases knowledge among the government, farmers, and the public about the environmental effects of untreated cassava mill effluents. The paper exposes to the government, environmentalists, policymakers, and the general public the problematic environment suffering from environmental pollution by cassava mill effluents and calls for prompt actions to mitigate its effects. The study creates awareness about possible measures to cushion the effects of cassava effluent on the environment, which include the new developments of channeling cassava effluents into cemented ditches for apt treatment and discharge and the zoning of cassava factory sites for effective control and management that guarantee sustainable development. It would significantly grant the researchers the privilege to make relevant contributions to areas with similar problems. It is an eye-opener for the public to realize that environmental elements do not exist in isolation, and what affects any individual species affects others as noted in ecosystem concept.. The research creates awareness that CME contributes to climate change. Furthermore, the paper creates the awareness that hydrogen cyanide in CME could cause neurological disorders, including partial blindness in humans. It also raises knowledge on the significance of applying red oil to cassava flour while processing it to reduce the toxic content of cassava cyanide in the CME.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval:\u0026nbsp;\u003c/strong\u003eThe ethics committee/examination panel chaired by the dean of the Faculty of the Social sciences University of Nigeria Nuskka approved the research\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate:\u0026nbsp;\u003c/strong\u003eThe authors confirm they sought and got the consent from all participants in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u003c/strong\u003e All named authors in the paper have mutually agreed that the manuscript be submitted to ESPR for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eMatthew Ogorchukwu \u003cstrong\u003eIsimah\u003c/strong\u003e: Conceptualization, method, Analysis, Writing- Original draft. Gladys Ogochukwu\u0026nbsp;\u003cstrong\u003eChukwurah\u003c/strong\u003e: method, analysis, writing- secondary Francis Ogochuwku\u0026nbsp;\u003cstrong\u003eOkeke\u003c/strong\u003e: draft, review, and validation of results, draft reviewing, and final editing.\u0026nbsp;Chukwuemeka Ifedilichukwu \u003cstrong\u003eNnoli\u003c/strong\u003e: Data collection, reviewing, and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research did not have the courtesy of any funding from any organization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials, available at the behest of the first author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbu J.O, Badifu G.O, Akpapunan M.A. (2006). Effect of Crude Palm - Oil Inclusions on some Physicochemical Properties of Gari, Fermented Cassava Food Product\u003cem\u003e. J. Food Sci. Technol\u003c/em\u003e. 24:73-79. \u003c/li\u003e\n\u003cli\u003eAdeniji A.A., Ega L.A., Akoroda M.O., Adeniyi A.A., Ugwu B.O., and Balogun A. (2005). Department of Agriculture Federal Ministry of Agriculture and Natural Resources Nigeria. FAO; Cassava Development in Nigeria.\u003c/li\u003e\n\u003cli\u003eAl-Rabaani A. and Al-Shuili A. (2020). Environmental Knowledge, Attitudes, and Behavior among Omani Post-Basic Education Students. European Journal of Social Sciences ISSN 1450-2267 Vol. 60 No 1 July, pp. 29-38.\u003c/li\u003e\n\u003cli\u003eBallew M., Marlon J, Leiserowitz A., and Maibach E. (2018). Gender Differences in Public Understanding of Climate Change Note \u0026middot;\u003c/li\u003e\n\u003cli\u003eCharacteristics of Soil Receiving Cassava Effluent in Elele, Rivers State, Nigeria. \u003cem\u003eJ Appl Environ Microbiol\u003c/em\u003e. 3: 20-24.\u003c/li\u003e\n\u003cli\u003eChinyere, G.C, Nwaogwugwu, C.J., Akatobi, K.U., Osuocha, K.U. (2018). Influence of Cassava Mill Effluent (CME) Dumping On Soil Physicochemical Parameters And Selected Plant Nutrientsin Uturu, Abia State Nigeria. \u003cem\u003eGlobalscientificjournal ( GSJ):\u003c/em\u003e Volume 6, Issue 1, January.\u003c/li\u003e\n\u003cli\u003eConstantini E and Hanf K. 1972. Environmental Concern and Lake Tahoe: A Study of Elite Perceptions, Backgrounds and Attitudes. Environ Behav. 4:209\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eDane, B. (2006). Likert Scales are the Meaning of life. Topic Report. CPSC681. pp. 1-10. \u003c/li\u003e\n\u003cli\u003eEhiagbonare, J. E., Enabulele, S. A., Babatunde, B. B., and Adjarhore, R. (2009). Effect of Cassava Effluents on Okada Denizens. Scientific Research and Essay, 4(4), 310 \u0026ndash; 313. \u003c/li\u003e\n\u003cli\u003eElijah A I, Popoola O, A R and Uzochukwu S V A. (2014). Molecular Characterization and Potential of Bacterial Species Associated with Cassava Waste\u003cem\u003e, Nigerian Food Journal\u003c/em\u003e 32(2), 56-65.\u003c/li\u003e\n\u003cli\u003eEze V. C. and Onyilide D. M.. Microbiological and Physicochemical Characteristics of Soil receiving Cassava Effluent in Elele, Rivers State, Nigeria. \u003cem\u003eJournal of Applied \u0026amp; Environmental Microbiology\u003c/em\u003e. 2015; 3(1):20-24. doi: 10.12691/jaem-3-1-4 \u003c/li\u003e\n\u003cli\u003eEze, A. V. and Nwibo, S. U. (2014). Economic and Technical Efficiency of Cassava Production in Ika North East Local Government Area, of Delta State, Nigeria. \u003cem\u003eJournal of Development and Agricultural Economics\u003c/em\u003e. Vol. 6(10), pp. 429-436, DOI: 10.5897 /JDAE2013.0541.\u003c/li\u003e\n\u003cli\u003eEzeigbo O R, Ike-Amadi, C A Okeke U P, Ekaoko M U (2014). The Effect of Cassava Mill Effluent on Soil Microorganisms in Aba, Nigeria\u003cem\u003e, International Journal of Current Research in Bioscience and Plant Biology\u003c/em\u003e 1(4), pp21-26. \u003c/li\u003e\n\u003cli\u003eFajemisin E., Ogungbemi S. E. and Tunde A. A. (2021). Partially-Processed Cassava Tubers on Poor Eye Vision in Nigeria: Impacts and Solutions. \u003c/li\u003e\n\u003cli\u003eFAO and IFAD, (2001). Strategic Environmental Assessment: An Assessment of the Impact of Cassava Production and Processing on the Environment and Biodiversity. Proceedings of the Validation Forum on the Global Development Strategy, April 10-12, Rome, Italy.\u003c/li\u003e\n\u003cli\u003eIzah S.C, Bassey S.E, Ohimain E.I (2017). Assessment of Heavy Metal in Cassava Mill Effluent Contaminated Soil in a Rural Community in the Niger Delta Region of Nigeria. EC Pharmacology and Toxicology 4(5): 186-201.21.\u003c/li\u003e\n\u003cli\u003eIzah S.C, Bassey S.E, Ohimain E.I (2017). Cyanide and Macro-nutrients Content of Saccharomyces Cerevisiae Biomass Cultured in Cassava Mill Effluents. \u003cem\u003eInternational Journal of Microbiology and Biotechnology\u003c/em\u003e 2(4): 176-180.24. \u003c/li\u003e\n\u003cli\u003eIzah S.C, Bassey S.E, Ohimain E.I (2017). Geo-accumulation Index, Enrichment Factor and Quantification of Contamination of Heavy Metals in Soil Receiving Cassava Mill Effluents in a Rural Community in the Niger Delta Region of Nigeria. Molecular Soil Biology 8(2): pp7-20.\u003c/li\u003e\n\u003cli\u003eIzah SC, Bassey SE, Ohimain El. (2017) Removal of heavy metals in cassava mill effluents by saccharomyces cerevisiaeisolated from palm wine. MOJ Toxicol.;3(4):83\u0026ndash;87. DOI: 10.15406/mojt.2017.03.00058\u003c/li\u003e\n\u003cli\u003eIzah S.C, Bassey S.E, Ohimain E.I (2018). Ecological Risk Assessment of Heavy Metals in Cassava Mill Effluents Contaminated Soil in a Rural Community in the Niger Delta Region of Nigeria. Molecular Soil Biology.\u003c/li\u003e\n\u003cli\u003eIzah S.C, Bassey S.E, Ohimain EI (2018). Impacts of Cassava Mill Effluents in Nigeria. \u003cem\u003eJournal of Plant and Animal Ecology\u003c/em\u003e 1(1): 14-42.2.\u003c/li\u003e\n\u003cli\u003eIzah S.C, Bassey SE, Ohimain E.I (2017). Assessment of some Selected Heavy Metals in Saccharomyces Cerevisiae Biomass Produced from Cassava Mill Effluents. EC Microbiology 12(5): 213-223.23. \u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez-Borreguero G., Maestre-Jimenez J., Mateos-N\u0026uacute;\u0026ntilde;ez M., and Naranjo-Correa F.L (2020). Analysis of Environmental Awareness, Emotions and Level of Self-Efficacy of Teachers in Training within the Framework of Waste for the Achievement of Sustainable Development. \u003cem\u003eSustainability\u003c/em\u003e. DOI: 10.3390/su12062563.\u003c/li\u003e\n\u003cli\u003eNdife J., Nwaubani O. and Aniekpeno I. E. (2019). Effect of Palm Oil Inclusion on the Quality of Garri Produced from White and Yellow Cassava (\u003cem\u003eManihot esculenta cranz\u003c/em\u003e) Roots. \u003cem\u003eInternational Journal of Food Science and Nutrition . \u003c/em\u003eVolume 4; Issue 3; May 2019; pp180-185. ISSN: 2455-4898 \u003c/li\u003e\n\u003cli\u003eNwaugo V.O., Chima G.N., Etok C.A. and Ogbonna C.E. 2008. Impact of Cassava Mill Effluent (CME) on Soil Physicochemical and Microbial Community Structure and Functions. Nig J Microbiol., 22: 1681-1688.\u003c/li\u003e\n\u003cli\u003eNwokoro, O., Anya, F. O., and Eze, I. C. (2013). The Use of Microorganisms in Increasing the Protein Yield of Cassava (Manihot esculenta Crantz) Peel Wastes. Polish Journal of Chemical Technology, 15(2), 112 \u0026ndash; 115. \u003c/li\u003e\n\u003cli\u003eObueh H.O, Odesiri-Eruteyan E. (2016). A Study on the Effects of Cassava Processing Wastes on the Soil Environment of a Local Cassava Mill. J Pollut Eff Cont 4: 177. doi: 10.4176/2375-4397.1000177.\u003c/li\u003e\n\u003cli\u003eOdoabuchi, V.E., Ejiogu, C.C., Nwanya, E., and Azubuike, C. (2020). Effect of Cassava Mill Effluent on Microbial Properties of Garden Soil: Eziobodo Imo State NIGERIA. \u003cem\u003eInternational Journal of Environment and Pollution Research\u003c/em\u003e Vol.8, No.3, pp.1-17. \u003c/li\u003e\n\u003cli\u003eOghenejoboh1 K. M. (2015). Effects of Cassava Wastewater on the Quality of Receiving Water Body Intended for Fish Farming. 6(2): 164-171, Article no.BJAST.2015.077 ISSN: 2231-0843.\u003c/li\u003e\n\u003cli\u003eOhimain E.I, Izah S.C. (2017). A Review of Biogas Production from Palm Oil Mill Effluents using Different Configurations of Bio Reactors. Renewable and Sustainable Energy Reviews Volume 70, Pages 242-253\u003c/li\u003e\n\u003cli\u003eOkechi R.N , Chukwura, E.I , Azuwike CO, and Ihejirika C.E. (2011). The impact of cassava mill effluent on the total aerobic bioload and Physicochemical Properties of the Soil. \u003cem\u003eJournal of Biodiversity and Environmental Sciences (JBES)\u003c/em\u003e, Vol. 1, No. 6, p. 112-117. ISSN: 2220-6663.\u003c/li\u003e\n\u003cli\u003eOkeke, F. O., Eziyi, I. O., Udeh, C. A., \u0026amp; Ezema, E.C. (2020) City as Habitat: Assembling the fragile city. Civil engineering Journal 2020; 6(6):1143-1154. doi: http://dx.doi.org/10.28991/ cej-2020-03091536\u003c/li\u003e\n\u003cli\u003eOmomowo I O., et al. (2015). \u0026ldquo;Bacteriological Screening and Pathogenic Potential of Soil Receiving Cassava Mill Effluents\u0026rdquo;. \u003cem\u003eInternational Journal of Basic and Applied Science \u003c/em\u003e3.4 pp26-36.\u003c/li\u003e\n\u003cli\u003eRauwald K.S and Moore C.F. (2002). Environmental Attitudes as Predictors of Policy Support Across Three Countries. Environ Behav. 34:703\u0026ndash;9\u003c/li\u003e\n\u003cli\u003eRilwani, M.L. (2005).\u003cem\u003e \u003c/em\u003eStatistics\u003cem\u003e \u003c/em\u003efor Environmental and Social Sciences 11.Esa-way Computers 22-43.\u003c/li\u003e\n\u003cli\u003eSakellari M. and Skanavis C, (2013). Environmental Behaviour and Gender: An Emerging Area of Concern for Environmental Education Research. \u003cem\u003eJournal of Applied Environmental Education \u0026amp; Communication.\u003c/em\u003e Volume 12,\u003c/li\u003e\n\u003cli\u003eThe Nation Newspaper (2018). Eight deadliest diseases in Nigeria. Sept. 19\u003csup\u003eth\u003c/sup\u003e.\u003c/li\u003e\n\u003cli\u003eUgbomeh B. A. (2011). Household Size and Socio-economic Resource. A Case study of Ika North East L. G.A. Delta State Nigeria. \u003cem\u003eAn International Multi-Disciplinary Journal\u003c/em\u003e, Ethiopia Vol. 5 (1), Pp226-238. Serial No. 18, January, \u003c/li\u003e\n\u003cli\u003eUstun B. and Celep B. (2007). The Connection between Environmental Awareness and Socio-Economic and Cultural structure. WIT Transactions On Ecology and the Environment, Vol 102, WIT Press Sustainable Development and Planning III 623. doi:10.2495/SDP070602.\u003c/li\u003e\n\u003cli\u003eYamane, T. (1967).\u003cem\u003e \u003c/em\u003eStatistics\u003cem\u003e. \u003c/em\u003eAn\u003cem\u003e \u003c/em\u003eIntroductory\u003cem\u003e \u003c/em\u003eAnalysis, 2nd Edition, New York, Happer and Row. \u003c/li\u003e\n\u003cli\u003eZhu C., Cai Y., Gertz E. R., La Frano M. R Dustin J., Burnett D.J., and Burri B.J. (2015). Red Palm Oil-supplemented and Bio-fortified Cassava Gari Increase the Carotenoid and Retinyl Palmitate Concentrations of Triacylglycerol-rich Plasma in Women. Nutr. Res. Nov; 35(11): pp965\u0026ndash;974. \u003c/li\u003e\n\u003cli\u003eZiadat, A.H. (2010) Major factors contributing to environmental awareness among people in a third world country/Jordan. Environ Dev Sustain 12, 135\u0026ndash;145 https://doi.org/10.1007/s10668-009-9185-4 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"07879a38-7b2d-4e94-8e1b-d1e54c4b2b6b","identifier":"10.13039/501100000867","name":"Commonwealth Scholarship Commission","awardNumber":"NGCA-2020-76","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Leicester","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cassava mill, Effluent, Environmental Effects, and Pollution","lastPublishedDoi":"10.21203/rs.3.rs-6968127/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6968127/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe awareness of the effects of small-scale cassava mill effluents (CME) on the environment in Ika Northeast Local Government Area, Delta State, was investigated. The study observed dying plants, contaminated water, and an unpleasant odor around cassava processing sites where CME flows indiscriminately on land. These are indications of environmental pollution that could affect the health and wellness of residents. The study used interviews and observation for data collection, and 399 questionnaires were administered to the respondents using systematic random sampling. A student t-test, ANOVA, and Pearson\u0026rsquo;s correlation were employed with SPSS version 21. The study revealed that most respondents had no in-depth knowledge of the implications of cassava effluent on the environment. This study shows no significant difference between males and females in awareness of the effects of CME on the environment (as the value of t\u0026thinsp;=\u0026thinsp;2.267, P\u0026thinsp;=\u0026thinsp;.086). The result shows a significant variation in the awareness level of CME effects on the environment with age (P\u0026thinsp;=\u0026thinsp;.026, F\u0026thinsp;=\u0026thinsp;4.014). There was a positive correlation between environmental awareness and education, occupation, and income. The study found that CME causes land degradation, air pollution, and water contamination. Therefore, the paper recommends an awareness campaign to educate the public on the implications of cassava effluent on the environment and the need for proper channeling and treatment before discharge for effective control and management.\u003c/p\u003e","manuscriptTitle":"Awareness of the effects of Small-Scale Cassava Mill Effluent on the Environment in Ika North East Local Government Area, Delta State, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 11:09:59","doi":"10.21203/rs.3.rs-6968127/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d4c4a936-8f98-43ef-85fd-9e5c72836b73","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50535812,"name":"Environmental Policy"},{"id":50535813,"name":"Environmental Chemistry"},{"id":50535814,"name":"Behavioral Geography"}],"tags":[],"updatedAt":"2025-06-25T11:09:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 11:09:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6968127","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6968127","identity":"rs-6968127","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}