Understanding and predicting the impact of the global energy transition and the United Nations Sustainable Development Goals (SDGs) on global mineral demand and African supply is challenging. This study uses a resource nexus approach to investigate and analyze the impact of this transition on energy and water demand and CO2 emissions using three annual material demand scenarios. The results indicate that African mining will consume more energy by 2050, leading to an increase in cumulative demand for energy (from 98 to 14,577 TWh) and water (from 15,013 to 223,000 million m3), as well as CO2 emissions (1318 and 19,561 Gg CO2e). In contrast, only a modest increase in energy demand (207 TWh) will be required by 2050 to achieve the SDGs. Therefore, the African mining industry should reduce its energy consumption and invest more in the renewable energy sector to support the global energy transition.
Twenty varieties of improved sorghum were grown in Machache at the Department of Agricultural Research station, located (29˚22'60"S and 27˚52'0"E) in the central foothills of Lesotho in Maseru district. The varieties were planted in a randomized complete block design. At maturity, they were harvested, dried, threshed, milled and analyzed in the crop science laboratory at the National University of Lesotho. The proximate and mineral contents were analyzed from samples in a completely randomized design with three replicates. The proximate composition parameters measured were crude proteins, crude fiber, crude fat, moisture content, and carbohydrates. The minerals analyzed were, phosphorus, sodium, calcium, magnesium, potassium, copper, zinc, iron, and magnesium. The results showed the nutritional contents ranging from (4.7% - 16.16%), (0.35% - 2.10%), (1.25% - 4.00%), (71.60% - 84.06%), (5.53% - 10.18%), for protein, fat, fiber and carbohydrate, and moisture content, respectively. Mineral content ranged from (1342.96 - 3500.34 mg/kg), (25.97 - 185.25 mg/kg), (50.71 - 511.71 mg/kg), (29.35 - 4542.13 mg/kg), (577.19 - 3041.52 mg/kg), (0.25 - 4.07 mg/kg), (1.96 - 18.61 mg/kg), (67.14 - 122.96 mg/kg), (4.73 - 11.39 mg/kg) for phosphorus, sodium, calcium, magnesium, potassium, copper, zinc, iron, and manganese respectively. The following varieties were found to have the highest and appreciable amounts of nutrients and minerals that are crucial in the country diet;protein content was KARI Mtama 1, zinc, IESX 16 2533-SB-SSI-19, and iron IESX 16 2535-SB-SSI-34.
地球科学的研究成果通常记录在技术报告、期刊论文、书籍等文献中,但许多详细的地球科学报告未被使用,这为信息提取提供了机遇。为此,我们提出了一种名为GMNER(Geological Minerals named entity recognize,MNER)的深度神经网络模型,用于识别和提取矿物类型、地质构造、岩石与地质时间等关键信息。与传统方法不同,本次采用了大规模预训练模型BERT(Bidirectional Encoder Representations from Transformers,BERT)和深度神经网络来捕捉上下文信息,并结合条件随机场(Conditional random field,CRF)以获得准确结果。实验结果表明,MNER模型在中文地质文献中表现出色,平均精确度为0.8984,平均召回率0.9227,平均F1分数0.9104。研究不仅为自动矿物信息提取提供了新途径,也有望促进矿产资源管理和可持续利用。
