Assessment of CH4 and CO2 Emissions from a Gas Collection System of a Regional Non-Hazardous Waste Landfill, Harmanli, Bulgaria, Using the Interrupted Time Series ARMA Model

Borisova, Daniela; Kostadinova, G.; Petkov, G.; Dospatliev, Lilko; Ivanova, Miroslava; Dermendzhieva, Diyana; Beev, Georgi

doi:10.3390/atmos14071089

Cited by 3 publications

(1 citation statement)

References 71 publications

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“…Landfill gas is produced by the microbial degradation of municipal solid waste (MSW) [1,2]. It migrates along the path of least resistance and eventually diffuses into the surrounding atmosphere due to the combined effects of concentration and pressure differences [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Analytical Solution for One-Dimensional Gas Pressure Distribution Considering the Variation of Gas Permeability Coefficients with Burial Depth

Yu,

He,

Liu

et al. 2023

Atmosphere

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Landfill gas generated by municipal solid waste (MSW) landfills is the world’s third largest source of greenhouse gas emissions. Additionally, the accumulation of landfill gas in waste piles can trigger instability in landfill piles. Based on the exponential distribution pattern of the variation of gas permeability coefficients with burial depth measured in situ, this paper presents an analytical solution for landfill gas-pressure distribution that is more in line with on-site conditions and has been verified by numerical calculations. Compared with cases where the gas permeability coefficient of landfill piles remains constant, the consideration that the gas permeability coefficient of MSW decreases exponentially with increasing burial depth is more likely to cause the accumulation of landfill gas at the landfill bottom, leading to higher gas pressure that can be more than five times higher than that in the former case. Based on a numerical analysis of gas extraction simulations, constant pressure gas extraction is relatively more effective in that a relative pressure of −0.1 kPa can lower the gas pressure in almost the entire pile, while bottom drainage fails to completely collect landfill gas even using a flux of 10–30 times ML.

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Section: Introductionmentioning

confidence: 99%

Analytical Solution for One-Dimensional Gas Pressure Distribution Considering the Variation of Gas Permeability Coefficients with Burial Depth

Yu,

He,

Liu

et al. 2023

Atmosphere

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Prediction of Sunspot Number with Hybrid Model Based on 1D-CNN, BiLSTM and Multi-Head Attention Mechanism

Chen,

Liu,

Yang

et al. 2024

Electronics

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Sunspots have a significant impact on human activities. In this study, we aimed to improve solar activity prediction accuracy. To predict the sunspot number based on different aspects, such as extracted features and relationships among data, we developed a hybrid model that includes a one-dimensional convolutional neural network (1D-CNN) for extracting the features of sunspots and bidirectional long short-term memory (BiLSTM) embedded with a multi-head attention mechanism (MHAM) to learn the inner relationships among data and finally predict the sunspot number. We evaluated our model and several existing models according to different evaluation indicators, such as mean absolute error (MAE) and root mean square error (RMSE). Compared with the informer, stacked LSTM, XGBoost-DL, and EMD-LSTM-AM models, the RMSE and MAE of our results were more than 42.5% and 65.1% lower, respectively. The experimental results demonstrate that our model has higher accuracy than other methods.

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Interaction Between Methane and Carbon Dioxide Emissions Using Methane-Reducing Biocover

Siltumens,

Grinfelde,

Burlakovs

et al. 2023

SGEM International Multidisciplinary Scientific GeoConference� EXPO Proceedings

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Decomposition of solid waste in landfills causes global air pollution with methane, the most dangerous of the greenhouse gases. The emission potential of this gas is 28-36 times greater than that of CO2. With the help of methane-reducing Biocover, can find a solution to this problem. In this study, a biocover was developed in the laboratory to reduce methane emissions. When measuring the methane emissions of this biocover, data on the amount of carbon dioxide emissions were also obtained in parallel. The purpose of this study is to clarify the interaction between methane emission reduction and carbon dioxide emission flux. The laboratory experiment consisted of three parts. The first part was the creation of experimental tubes. Three experimental columns with a diameter of 160 mm and a height of 1500 mm were created. Active compost saturated with water at a thickness of 500 mm was used as a source of methane, a permeable layer of sand at a thickness of 300 mm was further formed and finally covered with biocover. Biocover represents 60% of fine-fraction waste, 20% of soil and 20% of compost. The second part was taking measurements. All measurements were performed with the Cavity Ring-Down Spectroscopy (CRDS) gas measurement device Picarro G2508. The third part was the analysis of the obtained data. The obtained data were analyzed by processing the data and obtaining the interaction between these gases. The experiment is planned to be continued by obtaining long-term emission data. This will help to develop more promising future approaches to reduce methane emissions from landfills. This research contributes to the understanding of sustainable environmental management practices and underscores the importance of a holistic approach to address multiple greenhouse gases simultaneously.

show abstract

Assessment of CH4 and CO2 Emissions from a Gas Collection System of a Regional Non-Hazardous Waste Landfill, Harmanli, Bulgaria, Using the Interrupted Time Series ARMA Model

Cited by 3 publications

References 71 publications

Analytical Solution for One-Dimensional Gas Pressure Distribution Considering the Variation of Gas Permeability Coefficients with Burial Depth

Analytical Solution for One-Dimensional Gas Pressure Distribution Considering the Variation of Gas Permeability Coefficients with Burial Depth

Prediction of Sunspot Number with Hybrid Model Based on 1D-CNN, BiLSTM and Multi-Head Attention Mechanism

Interaction Between Methane and Carbon Dioxide Emissions Using Methane-Reducing Biocover

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