The general health of life is directly influenced by water quality and in order to maintain a healthy community, sufficient attention should be paid to managing water quality. This paper develops a health, safety and environmental framework for water quality management in the Global South (GS) using Lagos, Nigeria as a case study. Water security and water pollution are critical problems to human health, economic and environmental activities and much so in GS. Contaminated drinking water from industrial wastes, chemicals, toxic substances and wastewater as a result of industrial and agricultural activities causes serious health challenges to human. Global North (GN) countries have however, significantly improved water quality from past decades and implemented policies affecting water quality management. Despite regulations and policies towards a sustainable water quality in the GS, industrial activities in big cities like Lagos, have contributed hugely to water bodies pollution through indiscriminate waste disposal. Inadequate implementation of policies and regulations still persist as a challenge for water quality management. Comparative study between the GS countries, i.e., Nigeria and the GN countries (i.e., Iceland and Sweden) reveals that the GN adopts a strict compliance and transparency level as a preventive management strategy in ensuring sustainable water quality management – this is significantly lacking in Lagos, Nigeria. Emphatically, regulatory bodies in Lagos and Nigeria as a whole should effectively and regularly monitor water quality for drinking purpose and on-site wastewater. Water treatment parameters and analysis should be taken as important aspect for water quality management. The consequent problems of water quality management in Nigeria, has affected her socio-economic tendencies. This paper insists on adopting a better framework that improves the health, safety and environment of people by improving water quality management practices. Future work will include the use of modern technological equipment for water quality analysis and the adoption of standard circular economy principles.

Authors: T.K. Olaniyi, N. Nwankwo, U.E. Idahose

Published in: World Congress on Sustainable Technologies (WCST-2023)

• Date of Conference: 13-15 November 2023
• DOI: 10.20533/WCST.2023.0012
• ISBN: 978-1-913572-64-8
• Conference Location: St Anne’s College, Oxford University, UK

Medical diagnosis can be done very effectively by applying knowledge discovery in medical databases. Data Mining is an effective technique used to extract knowledge from databases and also helps to generate unknown and hidden patterns from the information stored in the databases. Healthcare dataset used in this research is gestational women data taken during first trimester of the gestational period. Application of data mining algorithms in the gestational women dataset for predicting the risk of gestational diabetes is a newapproach in the research field. In order to perform data preprocessing for the gestational women dataset used in this research paper, equal width binning interval approach is used to discretize the continuous valued attributes. The desired width of the interval in the database is fixed after getting opinion from the medical experts. The discretized input values are given as input to the generated model. In this research, the process is done at two phases. In phase 1, the numerical attributes are converted into categorical values using discretization techniques and in phase 2, Apriori algorithm is applied to the database that generates association rules which are useful to identify general association in the gestational diabetes dataset. These generated association rules show the relationship among the measured attributes and also indicate the risk level of gestational diabetes.

Authors: Srideivanai Nagarajan, P. Ramasubramanian, S. Hariharan

Published in: World Congress on Sustainable Technologies (WCST-2021)

• Date of Conference: 7-9 December 2021
• DOI: 10.20533/WCST.2021.0012
• ISBN: 978-1-913572-41-9
• Conference Location: Virtual (London, UK)

Within the integrated steel production, pelletization is a technique to prepare raw materials for feeding usually the Blast Furnace and to re-use by-products. In the present work samples of Basic Oxygen Furnace slag, provided by an Italian steelworks, were treated by different physical separation techniques like magnetic separation. After selecting the appropriate slag quality characterization, studies have shown that the slag properties would be affected by handling and processing. The experimental tests involved crushing, grinding of samples followed by two steps of sieving to reach a grain size lower than 4 mm. The combination of different factors and best outcomes in magnetic separation showed an important role in the selection of particle size of 2 mm with higher iron and lower phosphorus amount. This investigation allowed good pellets production, leading to improve the Basic Oxygen Furnace slag management and to recover high-grade iron material to be recycled in metallurgical processes.

Authors: Vitantonio Colucci, Teresa Annunziata Branca, Valentina Colla, Lea Romaniello

Published in: World Congress on Sustainable Technologies (WCST-2017)

• Date of Conference: 11-14 December 2017
• DOI: 10.20533/WCST.2017.0012
• ISBN: 978-1-908320-78-0
• Conference Location: University of Cambridge, UK