Fuzzy logic-based modeling of the impact of industrial activities on the environmental status of an industrial estate in Nigeria

Industrial growth is being attributed with adverse environmental effects and has necessitated stricter environmental management policies. Formulating such policies is limited by the difficulty in understanding the trends of monitoring data. This study is aimed at the application of fuzzy comprehensive assessment (FCA) to integrate environmental contaminants in Agbara industrial estate, Nigeria, to measure the extent of impact of industrial activities on the host community. Samples of water, plants (Pteridium aquilinum, Sacciolepis africana, and Panicum maximum), soil, and sediments were collected within the estate. Water samples were analyzed for quality parameters using standard methods. Metals (Co, Cr, Cd, Cu, and Mn) were investigated in all the samples using an atomic absorption spectrophotometer. The data were modeled with FCA. The results showed Cr as the major contaminant (34–252?µgL^?1). High phosphate contributed to large plant growth in the area. FCA results showed that water samples were in the pristine classification; sediment samples were extremely impacted. The vegetation growth and the sediment precipitation were responsible for the cleaning-up of the pollutants discharged downstream. The FCA of the plants indicated high metal bioaccumulation and not only showed the plants’ phyto-remediation potential but also that the metals may pose threats to human health through the food web. The activities in the estate are contributing contaminants to the environment with potential negative effects.     

Using remote sensing technique to study soil sedimentation flow

Soils will behave differently when used for agriculture, forestry, and other purposes and must be managed differently. The difference is most evident in the Inverbrackie Creek catchment area in South Australia where the study reported in this article was conducted and where the soils are used extensively for grazing and dairy farming. This catchment covers an area of 8.38 km², comprising an undulating upland plain with irregularly high hills and broad interfluves. Previous information-gathering methods used to model the catchment's hydrologic activity have been derived from the downstream pluviographic point-source technique. The model input samples obtained by this technique are not truly representative of the catchment. The potential for using remote sensing color infrared imagery to delineate the areas contributing to soil sediment flow is demonstrated as a better alternative to obtaining representative samples to model this activity. This article reports on part of the work supported by the University Research Grant, University of Adelaide.     

Economic impacts of storm surge and the cost-benefit analysis of a coastal spine as the surge mitigation strategy in Houston-Galveston area in the USA

Mitigation and Adaptation Strategies for Global Change - Rapid population growth, urbanization, and concentration of valuable assets and strategic infrastructure in coastal regions make coastal...