CHAPTER 3:OIL SPILLS RISK MANAGEMENT SYSTEM: CHALLENGES AND PROSPECTS IN SOUTH ................... AFRICA
3.2 NEED FOR OIL SPILL RISK MANAGEMENT
With an increase in maritime transportation and exploration activities, so is the probability of oil spill accidents bearing potential damages to both the biodiversity and the socio-economics of coastal communities (Lee and Jung, 2015; den Boer et al., 2014). Biodiversity and livelihoods, particularly the low-income maritime-dependent population, are variables influenced by marine oil spills (de Andrade et al., 2010).
The relationship between these variables determines the severity of the vulnerability. In essence, diverse land use activities within coastal environments often result in conflicting priorities, whereby lagoons, aquaculture industry, agriculture, tourism harbours, archaeological sites and maritime industry demand different tolerance of environmental sensitivity. Generally, the combination of rich biodiversity and economic activities results in a fragile ecosystem highly vulnerable to oil spill events.
Marine fauna and flora and their habitats are sensitive to the impact of oil and the resultant clean- up measures, mitigation mechanisms and cleaning products. Intertidal areas, estuaries, plains, and mangroves are severely vulnerable to contamination from hydrocarbons and cleaning interventions (Azevedo et al., 2017).
There is a limitation of data to factually contextualise the impact of hydrocarbons on the benthic, mesopelagic and plankton species found in South African waters (Sink et al., 2010). This constraint is a result of the novelty of deep-sea exploration in the country. PetroSA collected limited data between 1999-2009 on offshore petroleum activities with surveys from FA-Platform.
The purpose of that study was to analyse the impact of petroleum on the petroleum-exclusive zone of the Agulhas Bank. The study recorded a perceptive 100 benthic fauna species and over 50 fish species within the Oribi-Oryx block. Physical disturbance resulting from the deep-sea activities rather than the direct effects of petroleum caused benthic organism habitat away from the wellhead (Sink et al., 2010; Cordes et al., 2016). Although this evidence is inconclusive, the only mesopelagic species recorded in the vicinity of the well-field were Kingklip Genypterus Capensis and Jacopever Helicolenus Dactylopterus (Sink et al., 2010). However, it must be acknowledged that this was the first study assessing the impact of hydrocarbons in the South African context. As such, the data falls short of considering severe oil spills scenarios. The deep- pelagic (at 200 metres-seafloor depth), composed of the mesopelagic and bathypelagic depth biota, is crucial in food web provision and has a socio- economic value. This value is perceptible because species such as tunas, cephalopods and other fish are harvested in the deep-pelagic biota (Drazen et al., 2020).
An incident such as the Macondo well blow-out in the Gulf of Mexico has provided crucial findings that may be reasonably applicable to the local context. Sutton et al. (2020) argue that a similar
deep-sea oil spill scenario shall adversely affect the largest marine ecosystem in the near-pristine South African offshore environment. Such spill may result in detrimental physical and biochemical injuries to the largest ecosystem from the toxicity of oil-dispersants mixture (Buskey et al., 2016).
Considering the current balanced ecological diel vertical migration between the mesopelagic and bathypelagic species (Sutton et al., 2020), an oil spill in either stratum will have multiple effects on the food web and ultimately on the productivity of the habitat.
While exposure to oil reduces productivity in corals (Girard and Fisher, 2018), bacterial species such as the Oceanospirillum and Cycloclasticus become resilient (Kleindienst et al., 2016).
However, numerous texa of plankton react differently based on the type of oil and the littoral capacity of the environment to self-clean (Fisher et al., 2016; Sink et al., 2010).
The most persistent oil products, such as Crude oils and Heavy Fuel Oils (HFO), often have the worst impact on the environment (Castanedo et al., 2009). Dispersants are usually effective in treating these oils subterraneously and on the sea surface (Socolofsky et al., 2015). The resultant toxicity of the chemical, rapid dispersal of contamination and increased bioavailability of oil to the deep-pelagic taxa are the effects of dispersants use (Cordes et al., 2016; Sutton et al., 2020). Abnormality in development, degeneration of tissues, and the inability of microorganisms to degrade oil are some of the impacts of dispersant (Kleindiesnst, 2016; Cordes et al., 2016).
The combined properties of the oil-dispersant mixture, sedimentological composition, and wave energy are crucial in determining the fate and the subsequent cost of an oil spill. Different authors (Whitehead et al., 2018; White et al., 2000; Richardson and Brugnone, 2018) have developed various economic valuation methods to determine oil spill-related damages. The complexities associated with economic vulnerability assessment determine a reasonable link of causation between the expense incurred and the contamination caused by the spill. The amalgamation of the incident response costs, and the resulting damages further requires a cost-benefit analysis.
In undertaking this analysis, debates as to whether economists should include non-commercial expenses such as loss of recreational activities and the indirect costs related to job losses into economic valuations continue (Whitehead et al., 2018; White et al., 2000).
Incidents such as the Spanish Prestige and the Gulf of Mexico’s Deep Horizon show how economic valuation for compensation can particularly be protracted (Loureiro et al., 2009;
Cousins, 2016). Following the Gulf of Mexico oil spill, the implicated company, BP, lost one third (US$62 billion) of its market size (Cousins, 2016). The decline in revenue and share prices, clean- up costs, and criminal and civil liabilities exacerbated these losses (Konso et al., 2017; Krauss, 2013).
The cargo carrier Seli 1, grounded in 2009 in Table Bay, off the coast of Cape Town, highlights the financial impacts of a shipping incident and the subsequent oil spill. In a mission to avoid financial
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liability, the shipowners had deserted the wreck, leaving the South African government to finance the oil spill response, wreck removal and rehabilitating oiled wildlife response (Solomons, 2009).
The Table Bay coastline has more than 300 wrecks, with most incidents occurring during the winter months (Werz, 2003). In addition to the prevailing weather conditions, the type of oil, the frequency of incidents, the receiving environment and the availability of clean-up resources all influence the risk of oils spill (Den Boer et al., 2014). To this effect, oil properties that determine the rate of evaporation, emulsification and oxidations are time reliant and will dictate the level of impact the spill will cause. Subsequently, the robustness of oil mass control and other mechanisms that include clean-up operations require time-cautious risk assessment tools such as the trajectory models.
Information from trajectory models such as the probability and first impact time of the spill is crucial in assessing the incident’s potential impact (Lee and Jung (2015). This basis can provide vital information for identifying sacrificial and areas for priority protection. A combination of experts’ judgements, quantitative (statistical) methods and, modelling is the preferred approach for risk assessment (IPIECA-OGP, 2013). The amalgamation of oil spill modelling within oil spill contingency plans is essential in risk assessment procedures and emergency response planning (IPIECA-OGP, 2013).
For example, the Angolan National Oil Spill Contingency Plan assesses oil spill risk by juxtaposing the occurrence probability of a particular activity (ship collision, well blow-out, accidental leaks from pipelines) with the geographical coordinates. This approach is more consistent with the mathematical process of hazard assessment than risk assessment because it does not consider other variables such as response capacity, possible impact, and element exposed (vulnerability) to the hazards (Cardona, 2013; Fortunato et al., 2017; ISDR, 2009).
Outputs from such assessment processes are crucial for emergency planning and in support of long-term spatial planning (Bagdanavičiūtė et al., 2018; Olita et al., 2011). Ultimately, the information resulting from various risk assessment tools determines the quality and vital in resource prioritisation. However, fair implementation of such a decision is primarily dependent on a well-coordinated risk management plan for oil spills with comprehensive actions to be implemented before, during, and after the incident. The flow of information and stakeholder coordination throughout the process is essential. Rapport building during preparedness stages allows for familiarity that may influence seamless decision making during response. During the response phase, on the other hand, an information and communication management system is a fundamental tool that allows stakeholders to weigh trade-offs for the required actions (de Andrade et al., 2010). Considering several and often conflicting objectives between maritime safety and environmental protection fraternities in responding to oil spill incidents, integrated information and communication management is invaluable. Pieri et al. (2018) recommends an inter-operable system with advanced abilities to process data from multiple sources and
disseminate it to relevant decision-makers for an advanced level of managing the risk in real-time.
In conceptualising risk management further, differentiation on whether it is the process or rather an ideal state one strives to reach has been raised. In essence, resilience and mitigation are terminologies associated with process development (Manyena, 2006). A “state of readiness and risk elimination” has a connotation that there is a destination, a point where one would declare a satisfactory level of risk being managed. For this study, however, resilience refers to one’s ability to withstand stressors by using available resources to enhance capacities and lessen vulnerability in complex systems, thereby reaching a new state of equilibrium and strive in the face of adversity (Aiena et al., 2016; Coetzee et al., 2016).
Managing the potentially severe impacts during the planning phase includes avoiding oil exploration and production activities in highly environmentally sensitive areas, diversifying economic activities, and extending marine protected areas rules (Dalton and Jin, 2010).
Considering that these activities are ongoing projects for managing oil spill risk, it is crucial to conceptualise resilience as a process within complex socio-ecologically linked systems (Coetzee et al., 2016).
Subsequently, to mitigate the risks, particular principles and a well-thought-through process must be satisfied. In oil spills, mitigation procedures refer to measures implemented for spills prevention, promotion of effective planning and management of exposed resources (Azevedo et al., 2017; Ribotti et al., 2019). The responsive abilities of environmentalists and scientists to clean and rehabilitate oiled seabirds may, for example, be understood as a mitigation measure.
However, the inability of the affected sea birds to reproduce post the incident indicates a lack of resilience (Wepener and Degger, 2012).
Ultimately, resource-need must be aligned to the severity of an incident with a detailed elaboration of efficient emergency strategies based on an environmental sensitivity atlas.
Generally, the development of marine oil spill contingency plans sets out a model to mobilise local and international resources without elevating the status of an incident to that of a disaster.
Risk is then managed if measures within the plan identify the proposed methodology for protecting valuable resources and mitigating oil dispersion.
In light of the literature review on marine oil spill risk management, the subsequent section describes the methods developed to analyse the applicability of the system in the South African context.