Purpose Nigeria, a prominent country in Sub-Sahara Africa, is plagued with a protracted, erratic and low power supply. The purpose of this paper is to present an experimental investigation of the noise levels and pollutants’ (CO, CO2 and particulate matter (PM2.5)) concentrations associated with the prevalent use of diesel-powered generators in the country. It is aimed to provide information on the level of gaseous, particulate and noise pollutants that are related to diesel-powered generators that could assist in policy formulation and create public awareness on the possible health risks. Design/methodology/approach Diesel-fueled generators (105) with age and installed capacity ranging from 0.5 to 14 years and 10 to 500 kVA, respectively, were engaged in this work at Sango area of Ogun State, Nigeria. Standard measuring instruments were placed at 1 m from the diesel-powered generators to determine the noise levels and concentrations of CO, CO2 and PM2.5. Findings Ranges of 72.6–115.6 dB, 19–198 ppm, 501–5,805 ppm and 221–492 µg/m3 for the noise level, CO, CO2 and PM2.5 concentrations, respectively, were obtained. Both the averages and ranges of the noise levels and pollutants’ concentrations were considerably higher than the recommended maximum limits. Thus, this study substantiated the pollution of ambient noise and air because of the operation of diesel-fueled generators. Furthermore, the health risks connected to the exposure to CO and PM2.5 as implied via the evaluation of the air quality index revealed very unhealthy and hazardous conditions, respectively. Research limitations/implications The measurement of the pollutants’ concentrations at the tips of the exhaust pipes of the diesel-powered generators was desirable but could not be achieved using manually logged devices. Nonetheless, adequate pollutants’ concentration data that satisfactorily represent the level of air pollution associated with diesel-fueled generators’ operations were obtained at around 1 m from the exhaust pipes. Practical implications The study provided additional knowledge on the levels of noise and pollutants, and the public health risks connected to the operations of diesel-powered generators that will be beneficial to the public and policymakers. Originality/value The results revealed a considerably high level of noise and air pollution, and the inherent environmental and public health problems connected to diesel-powered generators’ usage in Nigeria. This could serve as a viable tool for formulating environmental policy and providing the necessary societal awareness in this regard.

This research investigates the applicability of bentonite enhanced termite mound soil mixture as an alternative filter medium for paint industrial wastewater (PIWW) management in a constructed pilot-scale filtration tank with four different sections. The mixture of bentonite (BC) and termite mound soil (MS) used as the filter was proportioned by percentage weight as (100% MS), $${\text{(5\% BC}} + {\text{95\% MS),}}$$ (5\% BC + 95\% MS), $${\text{(10\% BC}} + {\text{90\% MS),}}$$ (10\% BC + 90\% MS), $${\text{(15\% BC}} + {\text{85\% MS)}}$$ (15\% BC + 85\% MS) and placed into four sections, respectively. The filter materials were compacted, cured and subjected to wastewater loading for 30 weeks. The results obtained from the analysis of the filtrate samples revealed that filter with 15% BC content generally exhibited high and effective pollutant removal efficiencies of 51.3%, 98.9%, and 72.7% for total dissolved solids, total suspended solids, and copper, respectively, while a maximum removal efficiency of 100% was recorded for lead, chromium and cadmium. The pollutants (TDS, TSS, Pb, Cr, Cu and Cd) concentrations of the treated PIWW were below the National Environmental Standards and Regulations Enforcement Agency permissible limits for discharge. Hence, the 15% bentonite and 85% termite mound soil mixtures are recommended for the small-scale paint industries as a point of use measure for effective pollutant removal. Its application would mitigate the degradation of environmental resources caused by indiscriminate disposal of untreated effluent.

Corrosion inhibition of water extract of Spondias mombin on low carbon steel in 0.5 M sulphuric acid was investigated in this paper. Fresh leaves, fruits and bark of this plant, washed properly, ground separately using small amount of distilled water to extract the juice at a ratio of 500 ml (distilled water) to 1 kilogram of plant were used for this experiment. Corrosion inhibitors of 0.4 g/ml, 1 g/ml and 2 g/ml were made from the filterate. Low carbon steel coupons suspended with twine inside 250 ml container of 0.5 M sulphuric acid in the presence of different concentrations of the extracts at room temperature for 35 days. The coupons were retrieved at 7 days interval, and the initial and final weights were recorded.  Inhibition efficiency for the leaves extract increased with concentration and got to its peak on the 7th day, that of the fruits extract initially increased with concentration until 1 g/ml after which there was a decline, its highest value was also recorded on the 7th day. The best inhibition efficiencies (in the range of 76.32% to 83.21%) for Spondias mombin water extract were observed in 0.4 g/ml bark extract throughout the days of the experiment, the highest being recorded on the14th day. It can be concluded that Spondias mombin water extract is a good corrosion inhibitor of low carbon steel in 0.5 M sulphuric acid at room temperature, with the best being the bark extract which inhibited for up to 35 days.

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Purpose – The purpose of this paper is to develop an expert system capable of assessing risk associated with manual lifting in construction tasks and proffer some first aid advices which are comparable with those obtainable from human experts. Design/methodology/approach – The expert system, musculoskeletal disorders – risk evaluation expert system (MSDs-REES), used Microsoft.Net C# programming language to write the algorithm of the fuzzy inference system with variables load, posture and frequency of lift as inputs and risk of low back pain as the output. The algorithm of the inference engine applied sets of rules to generate the output variable in crisp value. Findings – The result of validation, between the human experts’ calculated risk values and MSDs-REES-predicted risk values, indicated a correlation coefficient of 0.87. Between the predicted risk values generated using MSDs-REES and the existing package (MATLAB version 7.8), there was a strong positive relationship statistically with correlation coefficient of 0.97. Originality/value – The study provided a very simple expert system which has the ability to provide some medical-related injury prevention advice and first aid information for injury management, giving it a unique attribute over the existing applications.