Chitkara University School of Engineering and Technology, Chitkara University, Solan, Himachal Pradesh, 174103, India.
Ex-Department of Civil Engineering, Indian Institute of Technology (BHU), Varanasi, 221005, India.
Environ Sci Pollut Res Int. 2023 Apr;30(17):48654-48675. doi: 10.1007/s11356-023-26052-y. Epub 2023 Feb 28.
The electronic and electrical industrial sector is exponentially growing throughout the globe, and sometimes, these wastes are being disposed of and discarded with a faster rate in comparison to the past era due to technology advancements. As the application of electronic devices is increasing due to the digitalization of the world (IT sector, medical, domestic, etc.), a heap of discarded e-waste is also being generated. Per-capita e-waste generation is very high in developed countries as compared to developing countries. Expansion of the global population and advancement of technologies are mainly responsible to increase the e-waste volume in our surroundings. E-waste is responsible for environmental threats as it may contain dangerous and toxic substances like metals which may have harmful effects on the biodiversity and environment. Furthermore, the life span and types of e-waste determine their harmful effects on nature, and unscientific practices of their disposal may elevate the level of threats as observed in most developing countries like India, Nigeria, Pakistan, and China. In the present review paper, many possible approaches have been discussed for effective e-waste management, such as recycling, recovery of precious metals, adopting the concepts of circular economy, formulating relevant policies, and use of advance computational techniques. On the other hand, it may also provide potential secondary resources valuable/critical materials whose primary sources are at significant supply risk. Furthermore, the use of machine learning approaches can also be useful in the monitoring and treatment/processing of e-wastes. HIGHLIGHTS: In 2019, ~ 53.6 million tons of e-wastes generated worldwide. Discarded e-wastes may be hazardous in nature due to presence of heavy metal compositions. Precious metals like gold, silver, and copper can also be procured from e-wastes. Advance tools like artificial intelligence/machine learning can be useful in the management of e-wastes.
电子和电气工业在全球范围内呈指数级增长，有时由于技术进步，这些废物的处理和丢弃速度比过去更快。随着世界数字化（IT 部门、医疗、家庭等）应用电子设备的增加，也产生了大量废弃的电子垃圾。与发展中国家相比，发达国家的人均电子垃圾产生量很高。全球人口的扩张和技术的进步是导致我们周围电子垃圾量增加的主要原因。电子垃圾对环境构成威胁，因为它可能含有金属等危险和有毒物质，可能对生物多样性和环境产生有害影响。此外，电子垃圾的寿命和类型决定了它们对自然的有害影响，而不科学的处理方式可能会像在印度、尼日利亚、巴基斯坦和中国等大多数发展中国家那样，加剧威胁程度。在本综述论文中，讨论了许多有效的电子废物管理方法，例如回收、回收贵金属、采用循环经济概念、制定相关政策和使用先进的计算技术。另一方面，它也可能为有价值/关键的材料提供潜在的二次资源，而这些材料的主要来源存在供应风险。此外，机器学习方法的使用也可用于电子废物的监测和处理/加工。 要点：2019 年，全球产生了约 5360 万吨电子垃圾。废弃的电子垃圾由于含有重金属成分，可能具有危害性。金、银和铜等贵金属也可以从电子垃圾中提取。人工智能/机器学习等先进工具在电子废物管理中可能很有用。
