This study addresses the challenge of reducing "net" toxic pollutant discharge, specifically dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), while minimizing the energy consumption and costs associated with detoxification. Our research focuses on reintroducing fly ash and scrubber sludge (ASR) into a hazardous waste thermal treatment system equipped with gasification-intense low oxygen dilution (GASMILD) and an advanced air pollution control system (APCS). This approach yielded a remarkable PCDD/F removal efficiency exceeding 99.9% for both mass and toxic equivalent (TEQ), achieving a net destruction of PCDD/Fs within the system. The success can be attributed to the ASR material's richness in ultrafine particles, which act as nucleation cores during combustion, promoting particle growth and enhancing the capture of PCDD/Fs in the APCS. This leads to a significant reduction (over 93%) in both PCDD/F mass and World Health Organization-toxic equivalent (WHO-TEQ) concentration in the flue gas. While a phase transition of gaseous PCDD/Fs within the APCS caused a shift in the particle size distribution towards larger particles, the overall PCDD/F mass concentration in the stack emissions remained lower with ASR. Notably, the reintroduced PCDD/Fs tend to deposit in the nasal region of the respiratory tract, potentially reducing the health risks associated with deeper lung deposition. This research demonstrates the effectiveness of ASR in achieving net PCDD/F destruction within a GASMILD combustion system, offering a promising strategy for cleaner and more sustainable waste management practices. From a managerial perspective, this approach provides a cost-effective solution for PCDD/F mitigation, contributing to reduced emissions and improved public health.
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http://dx.doi.org/10.1016/j.wasman.2024.12.043 | DOI Listing |
Neurosurg Rev
January 2025
Department of Neurosurgery, King's College Hospital Foundation Trust, London, UK.
Minimally invasive parafascicular surgery (MIPS) with the use of tubular retractors achieve a safe resection in deep seated tumours. Diffusion changes noted on postoperative imaging; the significance and clinical correlation of this remains poorly understood. Single centre retrospective cohort study of neuro-oncology patients undergoing MIPS.
View Article and Find Full Text PDFLangenbecks Arch Surg
January 2025
Stockholm University, Stockholm, Sweden.
Introduction: Imposter syndrome (IS) refers to the psychological experience of imagining that one's achievements do not originate from one's own authentic competence. Surgeons are constantly faced with life-threatening decisions and can easily feel inadequate or insecure despite their years of training and experience. Imposter syndrome can distress surgeons at all career stages and has profound psychological and professional consequences.
View Article and Find Full Text PDFToxicol Pathol
January 2025
Charles River Laboratories, Edinburgh, UK.
Thyroid tissue is sensitive to the effects of endocrine disrupting substances, and this represents a significant health concern. Histopathological analysis of tissue sections of the rat thyroid gland remains the gold standard for the evaluation for agrochemical effects on the thyroid. However, there is a high degree of variability in the appearance of the rat thyroid gland, and toxicologic pathologists often struggle to decide on and consistently apply a threshold for recording low-grade thyroid follicular hypertrophy.
View Article and Find Full Text PDFSci Rep
January 2025
University Institute of Computing, Chandigarh University, Punjab, India.
Automatic Sign Language Recognition Systems (ASLR) offers smooth communication between hearing-impaired and normal-hearing individuals, enhancing educational opportunities for impaired. However, it struggles with "curse of dimensionality" due to excessive features resulting in prolonged training time and exhaustive computational demand. This paper proposes technique that integrates machine learning and swarm intelligence to effectively address this issue.
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January 2025
University of Connecticut, Storrs, CT, USA.
Printed Circuit Board (PCB) design reconstruction is essential for addressing part obsolescence, intellectual property recovery, compliance, quality assurance, and enhancing national capabilities. Traditional methods for PCB design extraction, both non-geometry-based and geometry-based, have limitations in accuracy, efficiency, and scalability. This paper presents an automated approach, combining image processing and machine learning, to achieve 3D semantic segmentation of PCB X-ray Computed Tomography (X-ray CT) images and subsequent netlist extraction.
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