Morphochemical investigation on the enrichment and transformation of hazardous elements in ash from waste incineration plants

Ali, Muhammad Ubaid; Liu, Yuan; Yousaf, Balal; Wong, Ming Hung; Li, Ping; Liu, Guijian; Wang, Ruwei; Wei, Yong; Lu, Muyuan

doi:10.1016/j.scitotenv.2022.154490

Cited by 5 publications

(3 citation statements)

References 38 publications

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“…Figure 2 illustrates the occurrence of REYs identified in amorphous phases. Despite not being an abundant group of minerals, sulfates deserve great environmental relevance as Fe/Al sulfates can contain several dangerous elements aggregated in sediments [74][75][76]. In La Guajíra, lower proportions of sulfates were detected than in Cesar, where concentrations of sulfates were detected in greater proportions (Table 1).…”

Section: Characteristics Identified In the Analyzed Samplesmentioning

confidence: 99%

Hazardous Elements in Sediments Detected in Former Decommissioned Coal Mining Areas in Colombia: A Need for Environmental Recovery

et al. 2023

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This study demonstrates an investigation into nanomineralogical and geochemical evolution for the detection of hazardous elements from old, abandoned coal mining deposits capable of causing negative environmental impacts. The general objective of this study is to evaluate the number of nanoparticulate chemical elements in sediments collected during the years 2017 and 2022 from deactivated coal mining areas in the La Guajíra and Cesar regions of Colombia. Sediments were collected and analyzed from areas that experienced spontaneous coal combustion (SCC). The analysis consisted of traditional mineralogical analysis by X-ray diffraction and Raman spectroscopy, nanomineralogy by field emission scanning electron microscope-FE-SEM, and high-resolution transmission electron microscope-HR-TEM (energy dispersive X-ray microanalysis system-EDS). The analyzed sediment samples contained high proportions of amorphous materials containing the chemical elements As, Cl, Hg, Mo, Pb, Sb, and Se. This study emphasizes the need to implement environmental recovery projects at former, now abandoned coal extraction areas located in the investigated region, as they have negative effects on the environment and human health across large regions.

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Section: Characteristics Identified In the Analyzed Samplesmentioning

confidence: 99%

Hazardous Elements in Sediments Detected in Former Decommissioned Coal Mining Areas in Colombia: A Need for Environmental Recovery

et al. 2023

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“…Cluster II keywords were largely made up of words such as "chemical elements", "incineration", and "pollution abatement". In Cluster II, the transformation of hazardous elements in ash from waste incineration plants was investigated [49], and using integrated strategies for MSWM may lead to a reduction in greenhouse gas emissions by 2050 [48].…”

Section: Municipal Solid Waste Management In the Worldmentioning

confidence: 99%

Bibliometric Analysis of Municipal Solid Waste Management Research: Global and South African Trends

Ndou

Rampedi

2022

Sustainability

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Municipal solid waste management has become one of the most important environmental management issues around the world. In this study, a bibliometric analysis of the literature related to municipal solid waste management from a global and South African perspective was performed using the software, VOSviewer. Relevant scientific literature was sourced from the Scopus database. Results showed that, globally, articles based on this topic started during the 1968–1969 period, whereas in South Africa such articles only appeared in 1996. The keyword analysis showed that most studies were related to waste-to-energy technologies, waste treatment, and other management aspects. Globally, emerging keywords representing new research areas were COVID 19-related waste streams, life-cycle assessments, and the role of municipal solid waste management in the circular economy. In contrast, South Africa’s prominent keywords were municipal solid waste, developing country, landfills, waste treatment, waste-to-energy technologies, pollution, greenhouse gas emissions, and others. Based on these results, and possible solutions to reduce the amounts of MSW generation rates, recommendations are made to bring South African research on par with international trends.

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“…Among them, waste incineration has been widely adopted in more and more countries and regions because of its advantages of "harmless, recycling and reduction" [4,5]. However, the waste incineration process has key problems, such as unstable combustion, incomplete combustion of pollutants, and easy birth of materials due to the complex composition and fluctuation of calorific value of waste [6,7]. The incinerator main steam parameter is an important indicator of combustion stability.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Main Parameters of Steam in Waste Incinerators Based on BAS-SVM

Chen¹,

Wang²,

Zhong³

et al. 2023

Sustainability

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The main steam parameters of a waste-to-energy plant are the key indicator of the safety and stability of its combustion process. Accurate prediction of the main steam parameters can help the control system to reasonably analyze the combustion conditions and, thus, to greatly improve the combustion efficiency. In this paper, we propose an optimized method for predicting the main steam parameters of waste incinerators. Firstly, a grey relational analysis (GRA) is used to obtain the ranking of the correlation degree between 114 characteristic variables in the furnace and the main steam parameters, and 13 characteristic variables are selected as model inputs. A Spearman-based time delay compensation method is proposed to effectively overcome the influence of time asynchrony on the prediction accuracy. At last, the beetle antennae search (BAS) optimized support vector machine (SVM) model is proposed. Taking advantage of the fast iteration of the beetle antennae search algorithm to find the key hyperparameters of the support vector machine, the optimized main steam parameter prediction model is finally obtained. The simulation results show that the prediction accuracy of this model is greatly improved compared with traditional neural network models, such as long short-term memory neural networks (LSTMs) and convolutional neural networks (CNNs), as well as a single SVM.

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Morphochemical investigation on the enrichment and transformation of hazardous elements in ash from waste incineration plants

Cited by 5 publications

References 38 publications

Hazardous Elements in Sediments Detected in Former Decommissioned Coal Mining Areas in Colombia: A Need for Environmental Recovery

Hazardous Elements in Sediments Detected in Former Decommissioned Coal Mining Areas in Colombia: A Need for Environmental Recovery

Bibliometric Analysis of Municipal Solid Waste Management Research: Global and South African Trends

Prediction of Main Parameters of Steam in Waste Incinerators Based on BAS-SVM

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