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Environmental Attitude of Drivers in Alimosho Local Government Area, Lagos, Nigeria Cover

Environmental Attitude of Drivers in Alimosho Local Government Area, Lagos, Nigeria

Open Access
|Jan 2022

Abstract

This study examined the environmental attitude of drivers towards vehicle emission. The survey design that employed a five point Likert scale questionnaire and administered to 402 respondents (drivers) generated the data analysed. Data analysis involved descriptive and regression statistical tools. The results suggest that there was significant association between respondents’ sex, occupation, education and their environmental attitudes. A greater percentage (87. 3%) of the respondents was slightly more likely to agree that emissions from cars and trucks have serious impact on air quality. Majority (57.5%) of the respondents who were civil servants appeared to possess positive (favourable) attitudes towards the influence of emissions on the environment. Logistic regression suggest that respondents’ sex, occupation, education and vehicle’s purpose, income, age and social group significantly predicted their environmental attitudes. The study concludes that most of the sample possessed positive (favourable) environmental attitude towards vehicle emissions. This suggests that the environmental attitude of drivers towards emissions is not responsible for poor air quality. The policy implications of the findings include the need for the adoption of the polluter-pay-principle to reduce the volume of vehicles on our road, the necessity of promoting mass public transportation (such as the BRT and LAGBUS) as a way of reducing vehicle emission. Finally, sensitization program through social groups and schools is imperative.

Language: English
Page range: 60 - 72
Submitted on: May 14, 2020
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Published on: Jan 18, 2022
Published by: University of Maribor
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Chinenye Lilian Okafor, Onipede Wusu, published by University of Maribor
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.