Site specific diel methane emission mechanisms in landfills: A field validated process based on vegetation and climate factors

Synergistic effects of vegetation and microorganisms on enhancing of biodegradation of landfill gas

The uncontrolled release of landfill gas represents a significant hazard to both human health and ecological well-being. However, the synergistic interactions of vegetation and microorganisms can effectively mitigate this threat by removing pollutants. This study provides a comprehensive review of the current status of controlling landfill gas pollution through the process of revegetation in landfill cover. Our survey has identified several common indicator plants such as Setaria faberi, Sarcandra glabra, and Fraxinus chinensis that grow in covered landfill soil. Local herbaceous plants possess stronger tolerance, making them ideal for the establishment of closed landfills. Moreover, numerous studies have demonstrated that cover plants significantly promote methane oxidation, with an average oxidation capacity twice that of bare soil. Furthermore, we have conducted an analysis of the interrelationships among vegetation, landfill gas, landfill cover soil, and microorganisms, thereby providing a detailed understanding of the potential for vegetation restoration in landfill cover. Additionally, we have summarized studies on the rhizosphere effect and have deduced the mechanisms through which plants biodegrade methane and typical non-methane pollutants. Finally, we have suggested future research directions to better control landfill gas using vegetation and microorganisms.

Municipal solid waste landfill: Evidence of the effect of applied landfill management on vegetation composition

Proper management of municipal solid waste (MSW) is crucial to avoid pollution, environmental impacts and threat to public health. The problem of MSW is mainly arising from inadequate landfill site management. The objective of this study was to evaluate the impact of management practices and environmental risks at two landfill sites. The landfills were subject to long-term (10 years) vegetation monitoring. The vegetation was assessed using a floristic survey of identified plant species. The vegetation analysis showed that significant differences existed between the two landfill locations, with neophytes, invasive and expansive species dominating on one of the landfill sites, which may be attributed to climatic and geomorphological differences between the two sites, but also to variations in landfill management. These environmentally problematic species can potentially spread from the landfill into adjacent ecosystems, displace native plants and degrade adjacent farmland areas. The study of vegetation monitoring data suggests that, in addition to other types of monitoring, landfills should be subjected to regular vegetation biomonitoring, too. Landfill management practices should target the regulation of unwanted species, create conditions that are favourable to native plant species and provide as early as possible the restoration of filled cells.

Diurnal landfill methane flux patterns across different seasons at a landfill in Southeastern US

Diurnal patterns of methane flux are examined at a landfill in the Southeastern US. Methane fluxes are measured by an eddy covariance (EC) tower during representative one-week periods in three seasons: summer, fall, and winter. Measured methane fluxes are compared with atmospheric pressure, temporal variation of atmospheric pressure, wind shear velocity, and air temperature. Landfill methane flux varies significantly with shear velocity and temporal changes in atmospheric pressure when the atmosphere is neutral. Under unstable atmospheric conditions, air temperature correlates best with methane flux, which is corroborated with an independent dataset of tracer correlation method (TCM) measurements for similar measurement periods. These field data support a mathematical model previously proposed to describe atmospheric effects on methane flux from landfills. The field data also indicate significant diurnal methane flux variations, with daytime fluxes up to 23 times greater than nighttime fluxes. Because the majority of historical TCM measurements of whole landfill methane flux are between 12 pm and 6 pm at this landfill, when daily emissions are highest because of atmospheric effects, average diurnal fluxes might have been overestimated by as much as 73%. Methane emissions are most representative of diurnal average emissions when atmospheric stability is near-neutral, which occurs in the late morning (∼11 am) and in the early evening (∼5 pm) at this site.

Methane oxidation in a landfill biowindow under wide seasonally fluctuating climatic conditions

In the current study, a pilot biowindow was constructed in a closed cell of a Canadian Landfill, undergoing high seasonal fluctuations in the temperature from -30 in winter to 35 in summer. The biowindow was filled with biosolids compost amended with yard waste and leaf compost with the ratio of 4:1 as the substrate layer. Two years of monitoring of methane (CH₄) oxidation in the biowindow led to remarkable expected observations including a thick, solid winter frost cover affecting gas exchange in winter and temperatures above 45 ℃ in the biowindow in late summer. A high influx compared to the reported values was observed into the biowindow with an average value of 1137 g.m^-2.d^-1, consisting of 64% of CH₄ and 36% of carbon dioxide (CO₂) in the landfill gas. The variations in the temperature and moisture content (MC) of the compost layer in addition to the influx fluctuations affected CH₄ oxidation efficiency; however, a high average CH₄ oxidation rate of 237 g.m^-2.d^-1 was obtained, with CH₄ being mostly oxidized at top layers. The laboratory batch experiments verified that thermophilic methane-oxidizing bacteria (MOB) were active throughout the study period and oxidized CH₄ with a higher rate than mesophilic MOB. The methanotrophic potential of the compost mixture showed an average value of 282 µmol.g^-1.d^-1 in the entire period of the study which is in the range of the highest reported maximum CH₄ oxidation rates. The adopted compost mixture was suitable for CH₄ oxidation if the MC was above 30%. The significance of MC variations on CH₄ oxidation rate depended on the temperature range within the biowindow. At temperatures below 2 ℃, between 29 and 31℃, and above 45 ℃, MC was not a controlling factor for mesophilic CH₄ oxidation.

Application of periodic parameters and their effects on the ANN landfill gas modeling

To reach a practical landfill gas management system and to diminish the negative environmental impacts from landfills, accurate methane (CH₄) prediction is essential. In this study, the preprocessing steps including minimizing multicollinearity, removal of outliers, and errors with missing data imputation are applied to enhance the data quality. This study is the first at employing periodic parameters in the two-stage non-linear auto-regressive model with exogenous inputs (NARX) with the aim of providing a convenient and precise approach to predict the daily CH₄ collection rate from a municipal landfill in Regina, SK, Canada. Using a stepwise procedure, various volumes of training data were assessed, and concluded that employing the 3-year training data reduced the mean absolute percentage error (MAPE) of the CH₄ prediction model by 26.97% at the testing stage. The favorable artificial neural network model performance was obtained using the day of the year (DOY) as a sole input of the time series model with MAPE of 2.12% showing its acceptable ability in CH₄ prediction. Using an only DOY-based model is especially remarkable because of its simplicity and high accuracy showing a convenient and effective approach in time landfill gas modeling, particularly for the landfills with no reliable climatic data.

Transport mechanisms and emission of landfill gas through various cover soil configurations in an MSW landfill using a static flux chamber technique

This study evaluated the transport mechanisms and emission rates of landfill gas (LFG) from 200- (vegetated with short grass), 300- (vegetated with short grass), and 450-mm-thick (non-vegetated) interim cover soils within a municipal solid waste landfill. LFG emission and diffusion mechanisms were evaluated using static flux chambers and laboratory-scale diffusion columns. Overall, the greatest CH₄ and CO₂ emissions were consistently observed from the 200-mm-thick cover soil with an average flux rate of 39.2 mg m^-2 h^-1 and 3.07 × 10³ mg m^-2 h^-1, respectively. In addition to CH₄ and CO₂, H₂S migration through a 450-mm interim cover soil was also evaluated. The H₂S emission rate was relatively more uniform at an average of 2.47 × 10^-5 mg m^-2 h^-1. Long-term LFG emission was predicted using an emission model based on a first-order decomposition rate equation and compared with the static flux chamber method. The field-measured CO₂, CH₄ and H₂S emissions were less than the estimated emissions from the emission model, by 22%, 85%, and 91%, respectively. Further, the diffusion coefficients of CH₄, CO₂, and H₂S for the interim cover soils were determined using a laboratory-scale diffusion column test and compared with a three-parameter diffusion model. The measured and estimated diffusion coefficients for the three landfill gases were within the 10% variation limits. Based on these findings, the LFG emission rate varied depending on the physical-chemical properties of the cover soil (e.g., cover thickness, moisture content, compaction ratio, uneven distribution of soil), organic material content and age of buried refuse, and seasonal environmental conditions (such as temperature). Test results showed that fugitive CH₄ emissions can be reduced one fourth by utilizing an appropriate cover soil (300-mm to 450-mm, CL) compared to cases with a thinner cover soil.

Application of a multi-stage neural network approach for time-series landfill gas modeling with missing data imputation

To mitigate the greenhouse gas effect, accurate and precise landfill gas prediction models are required for more precise prediction of the amount and recovery time of methane gas from landfills. When the study associates to greenhouse gas emissions problems, time series prediction models are of considerable interests, in which significant past records of gas data are required. This study is the first to specially impute the missing methane (CH₄) data for applying in time series artificial neural network (ANN) model in an attempt to predict daily CH₄ generation rate from a landfill in Regina, SK, Canada. Pre-processing was conducted on data to evaluate independent and significant meteorological input variables and provide suitable dataset for developing CH₄ generation models. A two-stage time series model proposed in this study was performed by missing data imputation at the first stage, followed by a neural network auto-regressive model with exogenous inputs (NARX) at the second stage. The model with 3 layers, 5 climatic variables and 9 neurons in the hidden layer was the optimal structure. This model shows the high performance in CH₄ prediction with the average index of agreement of 0.92 and the average mean absolute percentage error (MAPE) of 3.03% during the testing stage. Missing data imputation coupled with NARX method decreased the mean squared error (MSE) of the model by 84% (compared to Multilayer Perceptrons neural network model) in the testing period representing the effectiveness of missing data estimation coupling with time series ANN models in daily CH₄ generation prediction.

Full-scale experimental study of methane emission in a loess-gravel capillary barrier cover under different seasons

The methane emission in a loess-gravel capillary barrier cover (CBC) in winter and summer was investigated by constructing a full-scale testing facility (20 m × 30 m) with a slope angle of 14.5° at a landfill in Xi'an, China. Weather conditions, methane emission, gas concentration, temperature, and volumetric water content (VWC) in the CBC were measured. The temperature and moisture in the CBC showed a typical seasonal pattern of warm and dry in summer and cold and wet in winter. Accordingly, the maximum methane oxidation rate and methane emission were higher in summer. The mean methane influx and methane emission decreased significantly as the VWC increased beyond 40% (i.e., a degree of saturation 0.85) at a depth of 0.85 m, which was near the loess/gravel interface. At this depth, more water was presented in the loess layer in the downslope direction due to capillary barrier effects, which increased the upslope methane emission. More dominant methane emission in the middle- and upper-section of the CBC occurred in summer than in winter as there was less soil moisture to facilitate methane transfer. The LFG balance showed that a significant fraction of the loaded LFG was not accounted in the flux chamber measurements due to the preferential flow along the edges of the CBC. The maximum methane oxidation rate was 93.3 g CH₄ m^-2 d^-1, indicating the loess-gravel CBC could mitigate methane emissions after landfill closure.

Effects of plant radial oxygen loss on methane oxidation in landfill cover soil: A simulative study

Radial oxygen loss (ROL) by the spreading root systems of vegetation can improve soil aeration for subsequent oxidation of methane (CH₄) by microbes in landfill cover soils. This study proposes a theoretical model that elucidated the effects of ROL on microbial oxidation of CH₄ to understand landfill gas transportation and oxidation in landfill cover soils. Parametric analyses were conducted to investigate the effects of root depth, root architecture, and ROL rate on the CH₄ oxidation efficiency of landfill cover soils. The simulation results suggested that disregarding O₂ emissions by plants root systems could underestimate the CH₄ oxidation efficiency, especially when the water content ranged from 20% to 35%. Additionally, plants with a parabolic root architecture indicated 7-13% higher CH₄ oxidation efficiency than other root architectures, i.e., uniform, triangular, and exponential. The CH₄ oxidation efficiency increased rapidly at root depths less than 0.25 m. Therefore, plants characterized by a parabolic root architecture, longer root length, and higher ROL capacity should be selected as the preferred species for mitigating CH₄ emissions from landfills in humid areas.

Methane emissions from landfill: influence of vegetation and weather conditions

Vegetation plays an important role in CH₄ transport and oxidation in landfill cover soil. This study investigated CH₄ emission fluxes in two landfills with different surface coverage conditions and it found that the CH₄ emission fluxes presented spatial and temporal disparities. A significant discrepancy in CH₄ emission flux between day and night in areas covered with Kochia sieversiana indicated that enhanced diffusion induced by rising temperature was the main mechanism for CH₄ transport during daytime. A significant increase of CH₄ emission flux after the K. sieversiana and Suaeda glauca plants were cut indicated that these plants provide greater contributions to CH₄ oxidation than to CH₄ transport. Diel CH₄ emission flux was found closely correlated with the climatic conditions. Diffusion was determined as the main mechanism for CH₄ transport at daytime in bare area, mediated by solar radiation and air temperature. Diffusion and plant-mediated transport by convection was established as the main transport mechanism in areas covered with K. sieversiana. Our results further the understanding of both the CH₄ emission mechanism and the impact of vegetation on CH₄ oxidation, transport, and emission, which will benefit the development of a reliable model for landfill CH₄ emissions.

Impact of meteorological parameters on extracted landfill gas composition and flow

The objective of this study was to investigate the impact of four pre-selected meteorological parameters (barometric pressure, wind speed, ambient temperature and solar radiation) on recovered landfill gas (LFG) flow, methane (CH₄) content of the LFG and the recovered CH₄ flow by performing statistical correlation tests and a visual check on correlations in scatterplots. Meteorological parameters were recorded at an on-site weather station, while LFG data were recorded when entering the gas engine. LFG CH₄ concentration, LFG flow and CH₄ flow correlated highly with both barometric pressure and changes in barometric pressure, and the correlations were statistically significant. A higher correlation was observed when studying changes in barometric pressure in comparison to the absolute value of barometric pressure. LFG recovery data correlated highly and significantly with wind speed during winter, but not during summer. Ambient temperature and solar radiation were not major meteorological parameters affecting LFG recovery, as low correlation coefficients were observed between these two parameters and the LFG recovery data.

Monitoring of methane emission from a landfill site in daily and hourly time scales using an automated gas sampling system

Landfill sites are significant sources of methane gas globally. Understanding the temporal variabilities of methane emissions from landfill sites is necessary for estimating such emissions. In this study, an automated monitoring system was used to monitor methane emission flux and concentration on daily and hourly time scales at a landfill site. Measured methane emission fluxes were almost negligible in the studied area. However, methane concentration at landfill surface at nighttime was significantly higher than those in the daytime, which demonstrates the importance of investigating methane emissions at an hourly time scale, including during nighttime. The daily and hourly variations in methane concentration were well correlated with either soil temperature or volumetric water content near the surface. The obtained relations indicate that the automated monitoring system measurements can facilitate a more comprehensive understanding of the methane emission mechanisms at different time scales.

A Simulation model for estimating methane oxidation and emission from landfill cover soils

Quantification of methane (CH₄) oxidation and emission from landfill cover soils is important for evaluating measures to mitigate anthropogenic greenhouse gas emissions. In this study, a model that combines the multicomponent diffusive equation and Darcy's law, coupled with the dual Monod kinetic equation, was established to simulate CH₄ transport, oxidation and emission in landfill cover soils. Sensitivity analysis was performed to illustrate the influence of model parameters on CH₄ transport, oxidation and emission. The model was then applied to predict CH₄ emissions from several column experiments. The results of the sensitivity analysis showed that a high CH₄ oxidation rate can be obtained with a high V_max of cover soil, even for a low cover soil thickness, and that oxidation efficiency is constant when the thickness of the cover soil becomes greater than a threshold value. The simulated results fitted well with the measured values, confirming that the new model provides a reliable method for estimating CH₄ emissions from landfills.

A simulation model for methane emissions from landfills with interaction of vegetation and cover soil

Global climate change and ecological problems brought about by greenhouse gas effect have become a severe threat to humanity in the 21st century. Vegetation plays an important role in methane (CH₄) transport, oxidation and emissions from municipal solid waste (MSW) landfills as it modifies the physical and chemical properties of the cover soil, and transports CH₄ to the atmosphere directly via their conduits, which are mainly aerenchymatous structures. In this study, a novel 2-D simulation CH₄ emission model was established, based on an interactive mechanism of cover soil and vegetation, to model CH₄ transport, oxidation and emissions in landfill cover soil. Results of the simulation model showed that the distribution of CH₄ concentration and emission fluxes displayed a significant difference between vegetated and non-vegetated areas. CH₄ emission flux was 1-2 orders of magnitude higher than bare areas in simulation conditions. Vegetation play a negative role in CH₄ emissions from landfill cover soil due to the strong CH₄ transport capacity even though vegetation also promotes CH₄ oxidation via changing properties of cover soil and emitting O₂ via root system. The model will be proposed to allow decision makers to reconsider the actual CH₄ emission from vegetated and non-vegetated covered landfills.