Dr Babatunde Anifowose CEnv., MSPE, MEI, SFHEA holds a Diploma in Data Processing (Comp. Sci.), BSc and MSc degrees from the University of Lagos, Akoka-Nigeria and a PhD in Geography and Environmental Science from the University of Birmingham UK (funded by the Nigerian Government through the Petroleum Technology Development Fund: 2007-2010). Dr Anifowose’s research interest focuses primarily on the assessment and mitigation of environmental impacts across the oil and gas value chain including the social-environmental science nexus and specifically oil spill trajectory simulation/modelling on water particularly in an EIA context; and how these influence livelihoods and environmental sustainability. This complex issue requires a systematic understanding of hydrological and hydraulic parameters, inter alia, for input characterisation into models of specific river channel or coastal environment of interest to support optimal decision-making in the protection of environmental receptors and ecosystem services. Dr Anifowose’s expertise in this area has evolved over the years through research, external consulting and tailored residential training e.g. (a) Science of Oil Spills held at the NOAA campus in Seattle, Washington USA; and (b) Meshing and Hydrodynamic Modelling held at HR Wallingford, Oxford, UK. Much earlier in his career, Babatunde had training in the ‘Concepts of Oil Spill Fate and Transport Forecasting’ provided by US National Oceanic and Atmospheric Administration and ‘Slow Water and Fast Water Booming Techniques’ provided by the US Environmental Protection Agency both funded by the American Petroleum Institute. He is also interested in climate change issues (e.g. methane emissions from oil and gas facilities) and seasonal variation in river flow, hydraulic geometry principle, oil and gas transportation, GIS and environmental remote sensing. Given his computing/data processing background, Babatunde is keenly interested in the evolving research sub-discipline that deals with the applicability of digital technologies (e.g. Artificial Intelligence, Machine Learning etc.) in EIA processes.

Dr Anifowose is an invited peer-reviewer for a number of Elsevier Journals. He has been privileged to advise on an externally-funded project on oil spills and hydro-environmental implications; and, also served as specialist adviser to the CSC on the quality of scholarship applicants and their suitability for UK post-doctoral fellowships in the field of Environmental Science relating to oil pollution. He is a professional member of the British Hydrological Society (with the Institution of Civil Engineers), the Society of Petroleum Engineers (HSSE and Sustainable Development Technical Discipline), the Energy Institute, and has been a friend of the Transportation Research Board (TRB) of the US National Academies of Science’s committee on Transportation of Hazardous Materials – AT040 since 2008. Dr Anifowose is a Senior Fellow of the UK Higher Education Academy.

Environmental Impact Assessment (EIA) of Energy Projects incl. the application of digital technologies (Artificial Intelligence, Machine Learning etc.); Social-Environmental Science nexus of development project impacts in host communities; Oil spill modelling; Flow description for oil spill trajectory simulation; Hydraulic Geometry Principle; Oil and Gas Transportation; Oil and Gas EIA/EIS Quality; Environmental GIS and Remote Sensing; Projects, Facilities and Construction phase interaction with Environmental receptors

My research work experience dates back to about 18 years ago (year 2000-2001) on a World Bank commissioned project on Rural Travels and Rural Transport Infrastructure in the riverine areas of selected oil producing communities in Nigeria’s Niger- Delta. This project has inspired my research focus through the years and has further provoked the quest for greater understanding of why, despite the implementation of environmental assessment protocols in Nigeria, environmental problems still persist – especially oil spills in river systems and coastal environment. Research evidence supported by existing literature shows that very little is known about key environmental receptors in locations where oil and gas activities currently take place. Therefore, my research hopes to further advance our knowledge of the process regimes of key hydro-environmental parameters (e.g. Q, m³ s^-1; H, m; V, m s^-1; X-Sectional Area, m; SSC, mg L^-1; wind, m s^-1; salinity & temp.) surrounding major oil and gas infrastructure and their location-specific influence on oil behaviour which should ideally inform oil spill response and impact mitigation. My experience and literature evidence show that real-time response to oil pollution has been ineffective partly due to limited understanding of these parameters, especially in places where methodical data collection is erratic or at times non-existent.