Environment
Hamid Sarkheil; Shahram Alghasi; Ali Sadeghy Nejad
Abstract
Environmental degradation, particularly in marine ecosystems, has become a critical issue, due to industrial activities. Offshore areas are significantly impacted by the deep sea mining operations, leading to pollution and ecological imbalances. The existing environmental risk assessment models often ...
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Environmental degradation, particularly in marine ecosystems, has become a critical issue, due to industrial activities. Offshore areas are significantly impacted by the deep sea mining operations, leading to pollution and ecological imbalances. The existing environmental risk assessment models often fail to integrate the qualitative and quantitative data effectively, highlighting a significant research work gap. This work aims to address this gap by developing a comprehensive framework using the Bayesian Networks (BN), and the NETICA software to evaluate the risks associated with the installation of three-legged deep sea mining structures. The major goals are to systematically identify and prioritize the risks, and to develop effective mitigation strategies. The novelty of this work lies in its innovative use of the Bayesian modeling to combine the expert knowledge with the empirical data, providing a detailed categorization of risks into the low, medium, and high levels. The output parameters focus on the severity, likelihood, and detectability of risks. The results indicate that 40% of the habitat destruction risks are low, 46% fall within the ALARP region, and 14% are high, while the species destruction risks are 31% low, 50% ALARP, and 19% high. These findings guide the targeted mitigation measures to ensure effective protection of the offshore marine environment. Also the work concludes with a set of recommendations aimed at mitigating identified risks, and minimizing the environmental impacts. These include the implementation of advanced monitoring technologies, adoption of best management practices, and enforcement of stricter regulatory frameworks.
Akbar Esmaeilzadeh; Sina Shaffiee Haghshenas; Reza Mikaeil; Giuseppe Guido; Roohollah Shirani Faradonbeh; Roozbeh Abbasi Azghan; Amir Jafarpour; Shadi Taghizadeh
Abstract
Iran is one of the countries with the largest number of quarry mines in the world. Diamond cutting wire is usually used in quarries to cut dimension stone cubes, which is accompanied by hazardous events. Therefore, detecting and investigating the possible quarry risks is crucial to have a safe and sustainable ...
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Iran is one of the countries with the largest number of quarry mines in the world. Diamond cutting wire is usually used in quarries to cut dimension stone cubes, which is accompanied by hazardous events. Therefore, detecting and investigating the possible quarry risks is crucial to have a safe and sustainable mining operation. In mine exploitation, maintaining the safety of vehicles and increasing the knowledge of personnel regarding safety issues can considerably mitigate the number or radius of effect of hazards. Hence, the incidents and risks in the West-Azerbaijan quarries in Iran are investigated in this work. To do so, a list of the hazards and their descriptions are first prepared. Then the hazard risk rating is conducted using the Failure Modes and Effects Analysis (FMEA) method. The number of priorities is calculated for each incident based on probability, intensity, and risk detection probability. Finally, the main causes of risks in the studies quarries are identified. The results obtained show that the most likely dangers in dimensional stone mines in West Azerbaijan are diamond cutting wire breaking, rock-fall, and car accidents, with the priority numbers of 216, 180, and 135, respectively. These hazards can be mitigated by applying some preservative activities such as timely cutting wire replacement, utilizing an intelligent system for cutting tool control, necessary personal training, and considering some preservative points.
