Methane,a potent greenhouse gas with a global warming potential significantly higher than carbon dioxide,plays a critical role in climate change.Accurate predictions of its future concentrations are vital for understa...Methane,a potent greenhouse gas with a global warming potential significantly higher than carbon dioxide,plays a critical role in climate change.Accurate predictions of its future concentrations are vital for understanding and mitigating its environmental impact.For this reason,this paper presents a comparative analysis of deep learning models—Long Short-Term Memory(LSTM),Gated Recurrent Unit(GRU),CNN(Convolutional Neural Network)-GRU,and CNN-LSTM—for forecasting atmospheric methane concentrations through 2050.Leveraging historical data,each model's performance was evaluated using key metrics,including Mean Absolute Error(MAE)and Nash-Sutcliffe Efficiency(NSE).The results reveal that the CNNLSTM model achieved the highest accuracy,with the lowest MAE of 0.6567 and the highest NSE score of 0.933,indicating its superior capability in capturing the complexities of methane concentration trends.In contrast,the GRU model exhibited the poorest performance,with an MAE of 0.9667 and an NSE score of 0.844.Projections for 2050 indicate significant increases in methane levels,with maximum yearly concentrations expected to reach up to 2199.76 ppb,particularly under the CNN-LSTM model.These findings underscore the potential risks associated with rising methane concentrations,which could exacerbate global warming and its associated impacts.The study highlights the importance of employing advanced predictive models like CNN-LSTM to inform and enhance global climate change mitigation strategies.展开更多
High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration inf...High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition(VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy(TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively.展开更多
To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-...To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-SVM) multi-classifier and regression machine. For the forecasting model, the methane concentration can be considered as a nonlinear time series and the time series analysis method is adopted to predict the change in methane concentration using LS-SVM regression. For the forewarning model, which is based on the forecasting results, by the multi-classification method of LS-SVM, the methane hazard was identified to four grades: normal, attention, warning and danger. According to the forewarning results, corresponding measures are taken. The model was used to forecast and forewarn the K9 working face. The results obtained by LS-SVM regression show that the forecast- ing have a high precision and forewarning results based on a LS-SVM multi-classifier are credible. Therefore, it is an effective model building method for continuous prediction of methane concentration and hazard forewarning in working face.展开更多
Work face 3312 of coal mining in a colliery was taken as an example in which methane data in a series of locations was analyzed.For the purpose of data analysis, work face 3312 was divided into sections with 20 powere...Work face 3312 of coal mining in a colliery was taken as an example in which methane data in a series of locations was analyzed.For the purpose of data analysis, work face 3312 was divided into sections with 20 powered supports and some measur- ing-points in a section.Through analysis based on the sectional control volume model,the following points are concluded: (1) the location of gob air flow begins flow into coal face in 70 m away from the haulage gallery;(2) in the control volumes No.10 and No.30,the ra- tios of methane intensity from coal face into gob to the methane intensity in the corre- sponding control volume are 30% and 22%;(3) in the control volume No.50 to No.110,the ratios of methane intensity from gob into coal face to the methane intensity in the corre- sponding control volume are 4%,17%,22% and 53%,respectively.展开更多
It is important to study the methane transport phenomenon in a longwall panel under descensional ventilation conditions. In this paper the gob area is divided into a number of nodes to represent the rectangular percol...It is important to study the methane transport phenomenon in a longwall panel under descensional ventilation conditions. In this paper the gob area is divided into a number of nodes to represent the rectangular percolating elements. The connections between nodes (elements) become branches,so that a network can be formed. Using the mechanics of porous media fluid flow, the mathematical model of air and gas flows has been established. Based on the existing ground pressure theories,the porosity of the inhomogeneous porous media in the gob can be given. In computer simulation it is considered that air pressure and temperature are functions of position ; air density, viscosity, and natural ventilation pressure are functions of temperature,pressure and methane concentration,and the resistance varies with air density and viscosity. Finally,the calculation results are given to show the differences between ascensional and descensional ventilation methods.展开更多
In recent years,leakage from buried gas pipelines has been a frequent occurrence around the world.Leaked gas can quickly diffuse and accumulate in adjacent confined spaces,such as inspection wells,sewage pipes,and hea...In recent years,leakage from buried gas pipelines has been a frequent occurrence around the world.Leaked gas can quickly diffuse and accumulate in adjacent confined spaces,such as inspection wells,sewage pipes,and heat pipeline trenches,posing serious threats to people's lives and property in the event of fire.In this study,a large-scale experimental system was conducted to better understand how methane diffuses after an unintended leak from an underground pipe and how long the methane may take to dissipate in the soil and the adjacent underground confined space.A theoretical analysis is conducted of the seepage characteristics of methane gas in soil,and the experimental results indicate that the variation of methane concentration over time in soil and underground confined spaces is directly related to the distance between the test points and the leak holes.With an escalation in the gas flow rate,methane concentration progressively elevates within the same leakage time,demonstrating a decreasing augmentation rate.Once the air source has been cut off,the gas concentration in the underground confined space will maintain a stable state for a period time after reaching the peak value.Additionally,the time required to reach the lower and upper limits of dangerous concentration has an exponential relationship with the diffusion distance.Fitting curve equations have been drawn in all experimental scenarios.展开更多
High resolutionδ^(18)O and methane records over the last 2ka have been reconstructed from Dasuopu ice core recovered from the Himalayas.Analysis shows that theδ^(18)O record correlates well with the Northern Hemisph...High resolutionδ^(18)O and methane records over the last 2ka have been reconstructed from Dasuopu ice core recovered from the Himalayas.Analysis shows that theδ^(18)O record correlates well with the Northern Hemispheric temperature,Dunde ice core record,and with temperature record in eastern China.The warming trend detected inδ^(18)O record from the last century is similar to that during the Medieval warm period.There is a dramatic increasing in methane concentration in the Dasuopu ice core,which reached 1031 nmol?mol-1 in 1997.Moreover,methane concentration in the Dasuopu ice core is about 15%-20%higher than that in Antarctica and Greenland.There is a positive correlation between methane concentration andδ^(18)O in Dasuopu ice core.展开更多
Methane is the second largest anthropogenic greenhouse gas,and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks.Therefore,the monitoring of CH_(4)concentrat...Methane is the second largest anthropogenic greenhouse gas,and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks.Therefore,the monitoring of CH_(4)concentration changes and the assessment of underlying driving factors can provide scientific basis for the government’s policy making and evaluation.China is the world’s largest emitter of anthropogenic methane.However,due to the lack of ground-based observation sites,little work has been done on the spatial-temporal variations for the past decades and influencing factors in China,especially for areas with high anthropogenic emissions as Central and Eastern China.Here to quantify atmospheric CH_(4)enhancements trends and its driving factors in Central and Eastern China,we combined the most up-to-date TROPOMI satellite-based column CH_(4)(xCH_(4))concentration from 2018 to 2022,anthropogenic and natural emissions,and a random forest-based machine learning approach,to simulate atmospheric xCH_(4)enhancements from 2001 to 2018.The results showed that(1)the random forest model was able to accurately establish the relationship between emission sources and xCH_(4)enhancement with a correlation coefficient(R^(2))of 0.89 and a root mean-square error(RMSE)of 11.98 ppb;(2)The xCH_(4)enhancement only increased from 48.21±2.02 ppb to 49.79±1.87 ppb from the year of 2001 to 2018,with a relative change of 3.27%±0.13%;(3)The simulation results showed that the energy activities and waste treatment were the main contributors to the increase in xCH_(4)enhancement,contributing 68.00%and 31.21%,respectively,and the decrease of animal ruminants contributed-6.70%of its enhancement trend.展开更多
As a crucial component of urban lifeline projects,shallow-buried gas pipelines pose a significant threat to society and people’s lives,as well as property in the event of a leakage accident.To investigate the diffusi...As a crucial component of urban lifeline projects,shallow-buried gas pipelines pose a significant threat to society and people’s lives,as well as property in the event of a leakage accident.To investigate the diffusion mechanism of gas leakage out of pipelines,the CFD method is employed to establish a validated numerical model for gas diffusion in backfilled soil.The effects of operating pressure,burial depth,leakage direction of pipelines,and soil resistance coefficient were discussed.The calculated results indicate that the numerical model can accurately predicte the diffusion process and the resistance coefficient of methane in soil-sand,loam,and clay-based.It was found that the burial depth affects the speed of gas diffusion to the soil surface but has little impacts on the concentration distribution range.The diffusion process in the same type of backfilled soil was found very similar under varying pipeline operating pressures,though the pipeline pressure significantly impacts the diffusion range.The shape of the leaked gas cloud in the soil is affected by soil resistance,leak direction,and air buoyancy.A new diffusion model for methane leaking in soil was proposed by introducing two time-related concentration adjustment parameters to the existing natural gas diffusion model.The average error between the calculated results of the proposed diffusion model and the established numerical model was found to be within 10%.展开更多
Northern peatlands represent one of the largest biospheric carbon reservoirs in the world.Their southern margins act as new carbon reservoirs,which can greatly influence the global carbon dynamics.However,the Holocene...Northern peatlands represent one of the largest biospheric carbon reservoirs in the world.Their southern margins act as new carbon reservoirs,which can greatly influence the global carbon dynamics.However,the Holocene initiation,expansion and climate sensitivity of these peatlands remain intensely debated.Here we used a compilation of basal peat ages across six isolated peatlands at the southern margins of northern peatlands to address these issues.We found that the earliest initiation event of these peatlands occurred after the Younger Dryas(YD,12,800–11,700 years ago)period.The second initiation event and rapid expansion occurred since 5 ka cal.BP.The recession of East Asian summer monsoon(EASM)during the YD period and at around 5 ka cal.BP likely played a major role in controlling the initiation and expansion of these peatlands.The rapid expansion of these peatlands possibly contributed to the significant increases in atmospheric methane concentrations during the late Holocene because of the minerotrophic fens status and rapid expansion of them.These ecological processes are different from northern peatlands,indicating the special carbon sink and source implications of these peatlands in the global carbon cycle.展开更多
A low-cost fiber Bragg grating(FBG) sensing system for coal-mine security monitoring is proposed in this paper.Based on the coherence multiplexing(CM) and spatial division multiplexing(SDM) techniques,this hybrid sens...A low-cost fiber Bragg grating(FBG) sensing system for coal-mine security monitoring is proposed in this paper.Based on the coherence multiplexing(CM) and spatial division multiplexing(SDM) techniques,this hybrid sensing network can support more than 40 sensors for quasi-distributed detection.It is demonstrated experimentally that the multiplexed sensing signal of each sensor can be clearly distinguished by an optical low-coherence reflectometry(OLCR).Methane concentration is detected with maximum sensitivities of an intensity variation of 10.92% and a concentration variation of 1%,using a well-designed sensor structure.Strain and temperature are also detected by this system,which also exhibits good results in the experiment.展开更多
文摘Methane,a potent greenhouse gas with a global warming potential significantly higher than carbon dioxide,plays a critical role in climate change.Accurate predictions of its future concentrations are vital for understanding and mitigating its environmental impact.For this reason,this paper presents a comparative analysis of deep learning models—Long Short-Term Memory(LSTM),Gated Recurrent Unit(GRU),CNN(Convolutional Neural Network)-GRU,and CNN-LSTM—for forecasting atmospheric methane concentrations through 2050.Leveraging historical data,each model's performance was evaluated using key metrics,including Mean Absolute Error(MAE)and Nash-Sutcliffe Efficiency(NSE).The results reveal that the CNNLSTM model achieved the highest accuracy,with the lowest MAE of 0.6567 and the highest NSE score of 0.933,indicating its superior capability in capturing the complexities of methane concentration trends.In contrast,the GRU model exhibited the poorest performance,with an MAE of 0.9667 and an NSE score of 0.844.Projections for 2050 indicate significant increases in methane levels,with maximum yearly concentrations expected to reach up to 2199.76 ppb,particularly under the CNN-LSTM model.These findings underscore the potential risks associated with rising methane concentrations,which could exacerbate global warming and its associated impacts.The study highlights the importance of employing advanced predictive models like CNN-LSTM to inform and enhance global climate change mitigation strategies.
基金supported by the Project Grant from Heilongjiang Bayi Agricultural Reclamation University,Heilongjiang,China (No.XDB201813)。
文摘High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition(VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy(TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively.
基金Project 50674111 supported by the National Natural Science Foundation of China
文摘To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-SVM) multi-classifier and regression machine. For the forecasting model, the methane concentration can be considered as a nonlinear time series and the time series analysis method is adopted to predict the change in methane concentration using LS-SVM regression. For the forewarning model, which is based on the forecasting results, by the multi-classification method of LS-SVM, the methane hazard was identified to four grades: normal, attention, warning and danger. According to the forewarning results, corresponding measures are taken. The model was used to forecast and forewarn the K9 working face. The results obtained by LS-SVM regression show that the forecast- ing have a high precision and forewarning results based on a LS-SVM multi-classifier are credible. Therefore, it is an effective model building method for continuous prediction of methane concentration and hazard forewarning in working face.
文摘Work face 3312 of coal mining in a colliery was taken as an example in which methane data in a series of locations was analyzed.For the purpose of data analysis, work face 3312 was divided into sections with 20 powered supports and some measur- ing-points in a section.Through analysis based on the sectional control volume model,the following points are concluded: (1) the location of gob air flow begins flow into coal face in 70 m away from the haulage gallery;(2) in the control volumes No.10 and No.30,the ra- tios of methane intensity from coal face into gob to the methane intensity in the corre- sponding control volume are 30% and 22%;(3) in the control volume No.50 to No.110,the ratios of methane intensity from gob into coal face to the methane intensity in the corre- sponding control volume are 4%,17%,22% and 53%,respectively.
文摘It is important to study the methane transport phenomenon in a longwall panel under descensional ventilation conditions. In this paper the gob area is divided into a number of nodes to represent the rectangular percolating elements. The connections between nodes (elements) become branches,so that a network can be formed. Using the mechanics of porous media fluid flow, the mathematical model of air and gas flows has been established. Based on the existing ground pressure theories,the porosity of the inhomogeneous porous media in the gob can be given. In computer simulation it is considered that air pressure and temperature are functions of position ; air density, viscosity, and natural ventilation pressure are functions of temperature,pressure and methane concentration,and the resistance varies with air density and viscosity. Finally,the calculation results are given to show the differences between ascensional and descensional ventilation methods.
基金funded by the Research and Development Project of the Ministry of Housing and Urban-Rural Development of the People's Republic of China(Grant No.2022-K-167)the Tianjin Key Laboratory of Urban Gas Utilization,China(Grant No.KF-2023-01)the Jilin Province Youth Growth Technology Project,China(Grant No.20230508152RC).
文摘In recent years,leakage from buried gas pipelines has been a frequent occurrence around the world.Leaked gas can quickly diffuse and accumulate in adjacent confined spaces,such as inspection wells,sewage pipes,and heat pipeline trenches,posing serious threats to people's lives and property in the event of fire.In this study,a large-scale experimental system was conducted to better understand how methane diffuses after an unintended leak from an underground pipe and how long the methane may take to dissipate in the soil and the adjacent underground confined space.A theoretical analysis is conducted of the seepage characteristics of methane gas in soil,and the experimental results indicate that the variation of methane concentration over time in soil and underground confined spaces is directly related to the distance between the test points and the leak holes.With an escalation in the gas flow rate,methane concentration progressively elevates within the same leakage time,demonstrating a decreasing augmentation rate.Once the air source has been cut off,the gas concentration in the underground confined space will maintain a stable state for a period time after reaching the peak value.Additionally,the time required to reach the lower and upper limits of dangerous concentration has an exponential relationship with the diffusion distance.Fitting curve equations have been drawn in all experimental scenarios.
基金This work was supported by Ministry of Science and Technology of China(Grant No.G1998040811)Pre-Launching Project of 973+1 种基金Chinese Academy of Sciences(Grant No.KZCX2-301)Innovation Group Fund of the National Natural Science Fundation of China.
文摘High resolutionδ^(18)O and methane records over the last 2ka have been reconstructed from Dasuopu ice core recovered from the Himalayas.Analysis shows that theδ^(18)O record correlates well with the Northern Hemispheric temperature,Dunde ice core record,and with temperature record in eastern China.The warming trend detected inδ^(18)O record from the last century is similar to that during the Medieval warm period.There is a dramatic increasing in methane concentration in the Dasuopu ice core,which reached 1031 nmol?mol-1 in 1997.Moreover,methane concentration in the Dasuopu ice core is about 15%-20%higher than that in Antarctica and Greenland.There is a positive correlation between methane concentration andδ^(18)O in Dasuopu ice core.
基金supported by the National Natural Science foundation of China(No.42105117)the Natural Science Foundation of Jiangsu Province(No.BK20200802)supported by the National Key R&D Program of China(Nos.2020YFA0607501 and 2019YFA0607202)。
文摘Methane is the second largest anthropogenic greenhouse gas,and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks.Therefore,the monitoring of CH_(4)concentration changes and the assessment of underlying driving factors can provide scientific basis for the government’s policy making and evaluation.China is the world’s largest emitter of anthropogenic methane.However,due to the lack of ground-based observation sites,little work has been done on the spatial-temporal variations for the past decades and influencing factors in China,especially for areas with high anthropogenic emissions as Central and Eastern China.Here to quantify atmospheric CH_(4)enhancements trends and its driving factors in Central and Eastern China,we combined the most up-to-date TROPOMI satellite-based column CH_(4)(xCH_(4))concentration from 2018 to 2022,anthropogenic and natural emissions,and a random forest-based machine learning approach,to simulate atmospheric xCH_(4)enhancements from 2001 to 2018.The results showed that(1)the random forest model was able to accurately establish the relationship between emission sources and xCH_(4)enhancement with a correlation coefficient(R^(2))of 0.89 and a root mean-square error(RMSE)of 11.98 ppb;(2)The xCH_(4)enhancement only increased from 48.21±2.02 ppb to 49.79±1.87 ppb from the year of 2001 to 2018,with a relative change of 3.27%±0.13%;(3)The simulation results showed that the energy activities and waste treatment were the main contributors to the increase in xCH_(4)enhancement,contributing 68.00%and 31.21%,respectively,and the decrease of animal ruminants contributed-6.70%of its enhancement trend.
基金support from National Natural Science Foundation of China(No.52378488,and 52378487)the Jiangsu Province Science and Technology Program Special Funds(Key.R&D Program Social Development)Project(No.BE2022820).
文摘As a crucial component of urban lifeline projects,shallow-buried gas pipelines pose a significant threat to society and people’s lives,as well as property in the event of a leakage accident.To investigate the diffusion mechanism of gas leakage out of pipelines,the CFD method is employed to establish a validated numerical model for gas diffusion in backfilled soil.The effects of operating pressure,burial depth,leakage direction of pipelines,and soil resistance coefficient were discussed.The calculated results indicate that the numerical model can accurately predicte the diffusion process and the resistance coefficient of methane in soil-sand,loam,and clay-based.It was found that the burial depth affects the speed of gas diffusion to the soil surface but has little impacts on the concentration distribution range.The diffusion process in the same type of backfilled soil was found very similar under varying pipeline operating pressures,though the pipeline pressure significantly impacts the diffusion range.The shape of the leaked gas cloud in the soil is affected by soil resistance,leak direction,and air buoyancy.A new diffusion model for methane leaking in soil was proposed by introducing two time-related concentration adjustment parameters to the existing natural gas diffusion model.The average error between the calculated results of the proposed diffusion model and the established numerical model was found to be within 10%.
基金supported by the Science and Technology Development Plan of Jilin Province(Grant No.YDZJ202201-ZYTS471)the National Natural Science Foundation of China(Grant No.42071121)supported by“the Fundamental Research Funds for the Central Universities”(Grant No.2412022ZD023).
文摘Northern peatlands represent one of the largest biospheric carbon reservoirs in the world.Their southern margins act as new carbon reservoirs,which can greatly influence the global carbon dynamics.However,the Holocene initiation,expansion and climate sensitivity of these peatlands remain intensely debated.Here we used a compilation of basal peat ages across six isolated peatlands at the southern margins of northern peatlands to address these issues.We found that the earliest initiation event of these peatlands occurred after the Younger Dryas(YD,12,800–11,700 years ago)period.The second initiation event and rapid expansion occurred since 5 ka cal.BP.The recession of East Asian summer monsoon(EASM)during the YD period and at around 5 ka cal.BP likely played a major role in controlling the initiation and expansion of these peatlands.The rapid expansion of these peatlands possibly contributed to the significant increases in atmospheric methane concentrations during the late Holocene because of the minerotrophic fens status and rapid expansion of them.These ecological processes are different from northern peatlands,indicating the special carbon sink and source implications of these peatlands in the global carbon cycle.
基金Project(No.60707020) supported by the National Natural Science Foundation of China
文摘A low-cost fiber Bragg grating(FBG) sensing system for coal-mine security monitoring is proposed in this paper.Based on the coherence multiplexing(CM) and spatial division multiplexing(SDM) techniques,this hybrid sensing network can support more than 40 sensors for quasi-distributed detection.It is demonstrated experimentally that the multiplexed sensing signal of each sensor can be clearly distinguished by an optical low-coherence reflectometry(OLCR).Methane concentration is detected with maximum sensitivities of an intensity variation of 10.92% and a concentration variation of 1%,using a well-designed sensor structure.Strain and temperature are also detected by this system,which also exhibits good results in the experiment.
