Comprehensive assessment of food waste treatment emission reduction in China: a life cycle perspective.

Food waste (FW) treatment has attracted increasing attention since waste classification occurred in China. Analyzing the environmental and economic impacts of different FW treatment technologies is required. In this study, four FW treatments, i.e., anaerobic digestion, black soldier fly (BSF) bioconversion, composting, and landfill, were evaluated using life cycle assessment (LCA) and life cycle cost (LCC). LCA results show that anaerobic digestion outperforms the other technologies, while LCC results indicate anaerobic digestion has the lowest economic benefits ($5.16) and landfill has the highest ($14.22). Bioconversion has the highest product revenue ($37.98). FW anaerobic digestion followed by treating digestate and waste crude oil was employed to investigate the environmental differences between waste classification and mixed incineration. Digestate gasification and conversion of waste crude oil to biodiesel are found to be environmentally friendly, and waste classification outperforms mixed incineration. Furthermore, we explored national-level environmental emission reduction with anaerobic digestion as the dominant technology via increasing resource utilization rate and applying household FW disposers. Results display that a 60% resource utilization rate decreases the overall environmental impact by 36.68% compared with current situation, and treating household FW separately at the source can further lead to emission reduction. This study provides a reference for selecting FW technologies for countries worldwide from environmental and economic perspectives, as well as a direction of resource utilization for how to reduce environmental emissions from treating the total FW produced by all humanity.

Comparative study of electroplating sludge reutilization in China: environmental and economic performances.

Harmless disposal and reutilization of electroplating sludge (ES) attract growing interests due to the high content of heavy metals, which requires economical-affordable and environmentally friendly processing technologies. Main reutilization alternatives in China, i.e., acid leaching, bioleaching, smelting, ironmaking blast furnace co-processing (IBFC), and cement kiln co-processing (CKC), were evaluated and compared via life cycle assessment (LCA) and life cycle costing (LCC) methods. In addition, the heavy metal recovery potential of these scenarios was also evaluated to focus on the sustainable use of metal resources. LCA results show that acid leaching outperforms other scenarios due to the environmental benefits originating from recovering heavy metals, while smelting exhibits the worst due to high energy consumption. The environmental contribution analysis reveals that the product nickel sulfate has a significant positive impact on acid leaching and bioleaching scenarios, and energy consumption is the key factor for smelting, IBFC, and CKC. LCC results show that bioleaching outperforms others, while CKC performs the worst because only inorganic materials are utilized. Bioleaching has the lowest externality cost while CKC has the highest. The heavy metal recovery assessment indicates that bioleaching exhibits the greatest potential with recovery rates of 99%, 99%, 93%, 96%, and 95% for Cu, Cr, Ni, Zn, and Fe, respectively. In contrast, the target heavy metal recovery rate for both acid leaching and smelting is 93%. Acid leaching and bioleaching scenarios are more advantageous from a comprehensive comparison.

A review on emergency disposal and management of medical waste during the COVID-19 pandemic in China.

The surge of medical waste (MW) generated during the COVID-19 pandemic has exceeded the disposal capacity of existing facilities. The timely, safe, and efficient emergency disposal of MW is critical to prevent the epidemic spread. Therefore, this review presents the current status of MW generation and disposal in China and analyzes the characteristics and applicability of emergency disposal technologies. The results show that movable disposal facilities can dispose of infectious MW on site, even though most of their disposal capacity is at a low level (<5 t/day). Co-disposal facilities need to be reformed completely for emergency MW disposal, in which separate feeding systems should be taken seriously. Specifically, municipal solid waste (MSW) incineration facilities have great potential to improve emergency MW disposal capacities. For hazardous waste incineration facilities, compatibility of the wastes must be matched to the composition and calorific value of the waste. As for cement kiln, MW can only be used as an alternative fuel instead of a raw material for cement. Based on the environmental risk and technical adaptability, the six emergency MW disposal technologies are recommended to be prioritized as follows: movable microwave sterilization, movable steam sterilization, movable incineration, co-incineration with hazardous waste, co-incineration with MSW and co-disposal in cement kilns. Infectious MW, especially COVID-19 MW, should be prioritized for disposal by centralized and movable disposal facilities, while non-infectious MW can be disposed of using co-disposal facilities. All stakeholders should strengthen the delicacy management of the end-of-life stage of MW, including collection, classification, packaging identification, transportation, and disposal. Currently, it is necessary for centralized disposal enterprises to follow the emergency disposal operation flowchart. From a long-term strategic perspective, making full use of regional movable and co-disposal facilities in the megacities can effectively enhance the emergency MW disposal capacity.

Intelligence-Augmented Rat Cyborgs in Maze Solving.

Cyborg intelligence is an emerging kind of intelligence paradigm. It aims to deeply integrate machine intelligence with biological intelligence by connecting machines and living beings via neural interfaces, enhancing strength by combining the biological cognition capability with the machine computational capability. Cyborg intelligence is considered to be a new way to augment living beings with machine intelligence. In this paper, we build rat cyborgs to demonstrate how they can expedite the maze escape task with integration of machine intelligence. We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in fourteen diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.

Automatic Training of Rat Cyborgs for Navigation.

A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat's behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs.