Removal of harmful components from MSWI fly ash as a pretreatment approach to enhance waste recycling.

Municipal solid waste incineration (MSWI) fly ash contains many harmful components that may limit its potential for recycling. An effective pretreatment is therefore required before any recycling can be implemented. In this study, the effects of four pretreatment methods (water washing, CO2-aided washing, CO32--aided washing, and CO2 and CO32--aided washing) on the extraction behavior of chloride, sulfate, and heavy metals were evaluated. Water washing was found to be effective for the extraction of all easily and moderately soluble Cl-bearing salts, achieving Cl extraction ratios of 88%, 90%, and 96% for ash from Chongqing (CQ), Qingdao (QD), and Tianjin (TJ), respectively. Injection of CO2 during washing facilitated decomposition of the hardly soluble Cl-bearing salts, increasing the Cl extraction efficiency by 6% for CQ ash and 9% for QD ash. However, for the TJ ash that contained few insoluble Cl-bearing minerals, CO2 injection decreased the Cl extraction rate. The addition of CO32- had a negative influence on Cl extraction for all ashes, but it slightly promoted sulfate extraction. Despite the high Cl removal rate, only 23-37% of the sulfate and 0.1-12% of heavy metals were removed. Overall, water-based pretreatment, especially CO2-aided washing, significantly altered the physical, chemical, and mineralogical characteristics of the fly ash, making it more suitable for recycling. Consequently, the blending ratio of the fly ash for cement clinker manufacture increased from 0.2 to 0.3% in the raw ash to 3.5-5.5% in the treated ash, enabling the extensive use of ash materials.

COVID-19 Detection from X-ray Images using Multi-Kernel-Size Spatial-Channel Attention Network.

Novel coronavirus 2019 (COVID-19) has spread rapidly around the world and is threatening the health and lives of people worldwide. Early detection of COVID-19 positive patients and timely isolation of the patients are essential to prevent its spread. Chest X-ray images of COVID-19 patients often show the characteristics of multifocality, bilateral hairy glass turbidity, patchy network turbidity, etc. It is crucial to design a method to automatically identify COVID-19 from chest X-ray images to help diagnosis and prognosis. Existing studies for the classification of COVID-19 rarely consider the role of attention mechanisms on the classification of chest X-ray images and fail to capture the cross-channel and cross-spatial interrelationships in multiple scopes. This paper proposes a multi-kernel-size spatial-channel attention method to detect COVID-19 from chest X-ray images. Our proposed method consists of three stages. The first stage is feature extraction. The second stage contains two parallel multi-kernel-size attention modules: multi-kernel-size spatial attention and multi-kernel-size channel attention. The two modules capture the cross-channel and cross-spatial interrelationships in multiple scopes using multiple 1D and 2D convolutional kernels of different sizes to obtain channel and spatial attention feature maps. The third stage is the classification module. We integrate the chest X-ray images from three public datasets: COVID-19 Chest X-ray Dataset Initiative, ActualMed COVID-19 Chest X-ray Dataset Initiative, and COVID-19 radiography database for evaluation. Experimental results demonstrate that the proposed method improves the performance of COVID-19 detection and achieves an accuracy of 98.2%.

Thermal remediation of cyanide-contaminated soils：process optimization and mechanistic study.

Site soils with persistent cyanide compounds (primarily iron-cyanide complex) pose potential hazards to the environment and require remediation before redevelopment. This study evaluated the possibility of thermal treatment on remediation of cyanide-contaminated soils via batch heating experiments spanning a wide temperature range (200-500 °C). The change with operation variables of total cyanide and some reaction intermediates (e.g. CN-) was analyzed in order to elucidate the optimal variables that guarantee cyanide removal while generating no hazardous byproducts. Temperature, heating time and cyanide species have been found to be important parameters influencing removal/destruction of cyanide in soils. For soils bearing K3[Fe(CN)6] and K4[Fe(CN)6], a removal efficiency of >99.9% can be obtained with temperatures over 350 °C at 1 h, while for samples bearing Fe4[Fe(CN)6]3, a higher temperature (>450 °C) is needed to obtain an equivalent efficiency. During heating, the iron-cyanide complexes decomposed, releasing highly toxic free cyanides, which will subsequently be oxidized. However, a small percentage of free cyanide can always be detected as a result of incomplete oxidation, thus caution should be taken to minimize the accumulation of free cyanide during thermal treatment.