Spatial and temporal distribution of methane emissions from a covered landfill equipped with a gas recollection system

Gonzalez-Valencia, Rodrigo; Magaña-Rodriguez, Felipe; Martinez‐Cruz, Karla; Fochesatto, G. J.; Thalasso, Frédéric

doi:10.1016/j.wasman.2020.12.017

Cited by 7 publications

(5 citation statements)

References 41 publications

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“…Moreover, the model is not limited to fluxes data but can be applied to any quantitative or nonquantitative numerical parameter, although in that case, M ′ j no longer necessarily signifies a mass emitted per unit of time but a magnitude associated with the parameter under consideration. For further information regarding the NHM, please refer to previous studies that used a similar approach in aquatic ecosystems , and landfills. , …”

Section: Methodsmentioning

confidence: 99%

“…For further information regarding the NHM, please refer to previous studies that used a similar approach in aquatic ecosystems 30 , 31 and landfills. 32 , 33 …”

Section: Methodsmentioning

confidence: 99%

“…For further information regarding the NHM, please refer to previous studies that used a similar approach in aquatic ecosystems 30,31 and landfills. 32,33 To estimate the temporal and spatial variability of flux measurements at different times and locations, our main indicator was the mean coefficient of variation (CV), calculated as the ratio of the standard deviation to the mean. We first assessed the normality of the data using the Shapiro− Wilk test to ensure the validity of comparisons among parameters across locations and times.…”

Section: Data Treatment and Statisticalmentioning

confidence: 99%

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Fine-Scale Spatial Variability of Greenhouse Gas Emissions From a Subantarctic Peatland Bog

Riquelme del Río,

Sepulveda-Jauregui,

Salas-Rabaza

et al. 2024

Environ. Sci. Technol.

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Peatlands are recognized as crucial greenhouse gas sources and sinks and have been extensively studied. Their emissions exhibit high spatial heterogeneity when measured on site using flux chambers. However, the mechanism by which this spatial variability behaves on a very fine scale remains unclear. This study investigates the fine-scale spatial variability of greenhouse gas emissions from a subantarctic Sphagnum peatland bog. Using a recently developed skirt chamber, methane emissions and ecosystem respiration (as carbon dioxide) were measured at a submeter scale resolution, at five specific 3 × 3 m plots, which were examined across the site throughout a single campaign during the Austral summer season. The results indicated that methane fluxes were significantly less homogeneously distributed compared with ecosystem respiration. Furthermore, we established that the spatial variation scale, i.e., the minimum spatial domain over which notable changes in methane emissions and ecosystem respiration occur, was <0.56 m2. Factors such as ground height relative to the water table and vegetation coverage were analyzed. It was observed that Tetroncium magellanicum exhibited a notable correlation with higher methane fluxes, likely because of the aerenchymatous nature of this species, facilitating gas transport. This study advances understanding of gas exchange patterns in peatlands but also emphasizes the need for further efforts for characterizing spatial dynamics at a very fine scale for precise greenhouse gas budget assessment.

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Section: Methodsmentioning

confidence: 99%

“…For further information regarding the NHM, please refer to previous studies that used a similar approach in aquatic ecosystems 30 , 31 and landfills. 32 , 33 …”

Section: Methodsmentioning

confidence: 99%

Section: Data Treatment and Statisticalmentioning

confidence: 99%

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Fine-Scale Spatial Variability of Greenhouse Gas Emissions From a Subantarctic Peatland Bog

Riquelme del Río,

Sepulveda-Jauregui,

Salas-Rabaza

et al. 2024

Environ. Sci. Technol.

Self Cite

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“…There have been few studies that attempted to estimate mechanisms and the relative contribution of emissions of CH 4 from landfill sources [45][46][47][48]. An investigation of spatial and temporal variations of CH 4 fluxes from the landfill facilities with the use of interpolation methods was conducted by Haro et al [48], Gonzalez-Valencia et al [49] and Zhang et al [50]. In general, landfills are known to be a source of significant fugitive methane emissions, however, there is also a large spatial variability in CH 4 rates from similar sources in various locations across countries.…”

Section: Hydrolysis (In Thementioning

confidence: 99%

Assessment of GHG Interactions in the Vicinity of the Municipal Waste Landfill Site—Case Study

2021

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Landfills have been identified as one of the major sources of greenhouse gas (GHG) emissions and as a contributor to climate change. Landfill facilities exhibit considerable spatial and temporal variability of both methane (CH4) and carbon dioxide (CO2) rates. The present work aimed to evaluate the spatial distribution of CH4 and CO2 and their δ13C isotopic composition originating from a municipal landfill site, to identify its contribution to the local GHG budget and the potential impact on the air quality of the immediate surroundings in a short-term response to environmental conditions. The objective was met by performing direct measurements of atmospheric CO2 and CH4 at the selected monitoring points on the surface and applying a binary mixing model for the determination of carbon isotopic ratios in the vicinity of the municipal waste landfill site. Air samples were collected and analysed for isotopic composition using flask sampling with a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. Kriging and Inverse distance weighting (IDW) methods were used to evaluate the values at unsampled locations and to map the excess of GHGs emitted from the landfill surface. The large off-site dispersion of methane from the landfill site at a 500 m distance was identified during field measurements using isotopic data. The mean δ13C of the landfill biogas emitted to the surrounded atmosphere was −53.9 ± 2.2‰, which corresponded well to the microbial degradation processes during acetate fermentation in the waste deposits. The calculated isotopic compositions of CO2 (δ13C = −18.64 ± 1.75‰) indicate the domination of biogenic carbon reduction by vegetation surrounding the landfill. Finally, amounts of methane escaping into the air can be limited by the appropriate landfill management practices (faster covers active quarter through separation layer), and CH4 reduction can be achieved by sealing the cover on the leachate tank.

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“…Among the available non‐linear models for flux calculations, a regression‐based extension of a method proposed by Hutchinson and Mosier (1981), referred to as HMR, is among the most widely used. An advantage of this flux calculation method, developed by Pedersen et al (2010), is that it is available as part of an R package called “HMR” which has been used for flux estimations from widely different environments: freshwater marsh (Villa et al, 2021), a soil covered landfill (Gonzalez‐Valencia et al, 2021), buffer zones treating agricultural drainage water (Carstensen et al, 2021), bryophyte communities on the soil surface (Grau‐Andrés et al, 2021), forest soil (Martinez & Ardón, 2021) and, predominantly, agricultural soils (e.g. Glenn et al, 2021; Ruser et al, 2017; Tariq et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Identifying criteria for greenhouse gas flux estimation with automatic and manual chambers: A case study for N₂O

Pullens

Ábalos

Petersen

et al. 2023

European J Soil Science

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Fluxes of the powerful greenhouse gas nitrous oxide (N2O) are mainly quantified using manually operated or automatic non‐steady‐state chambers. With both systems, fluxes are calculated as the change in N2O concentration over time using linear or non‐linear regression, but the type of regression selected can have a strong influence on the N2O flux magnitude. The HMR package, a regression‐based implementation of the Hutchinson & Mosier Regression, is a widely used software for trace gas flux calculation that provides a recommendation on the most appropriate regression method based on several criteria. New parameters were recently introduced which allow for pre‐filtering based on sample variance (pfvar and pfalpha), and for constraining the curvilinearity of concentration‐time series(SatPct and SatTimeMin). Currently, there are no guidelines on how to choose the best parameters for specific user conditions. Here we address this knowledge gap using datasets from manual and automatic chambers, and sensitivity analyses. We found that the effect of parameter settings on the cumulative fluxes was greater for manual chamber data compared to the automatic chamber data, with ranges of up to 67.3% and 1.5%, respectively. The parameter pfvar was identified as highly sensitive for both manual and automatic chambers; it is, therefore, critical to select a threshold for when to allow for non‐linear flux calculation that accurately represents the given measurement precision. This can be estimated from the variance of N2O measurements at ambient concentration levels. The parameter SatTimeMin was critical for manual chamber data where the curvature is much less constrained due to the lower number of observations. The parameter pfalpha was the least sensitive and can be set at a p‐value equal to 0.05 following common statistical practice. Parameter values depend on the expected flux characteristics with a given chamber design and are currently best selected based on visual inspection of the data. This study identifies where and how specific care should be taken for the selection of parameters in the HMR package, which may contribute to standardizing the methodologies used worldwide for N2O flux calculations, supporting initiatives in which data from many studies need to be combined. Highlights The HMR package, an implementation of the Hutchinson & Mosier Regression, is a widely used software for trace gas flux calculation that provides a recommendation on the most appropriate regression method based on several criteria. New parameters in the updated HMR package constrains the use of nonlinear flux calculation and inclusion of outliers. The new parameters affect the cumulative emissions of N2O obtained with manual and automated chambers differently. We found that the choice of parameter values led to differences in cumulative N2O emissions of up to 67.3% This study identifies where and how specific care should be taken for the selection of parameters.

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Spatial and temporal distribution of methane emissions from a covered landfill equipped with a gas recollection system

Cited by 7 publications

References 41 publications

Fine-Scale Spatial Variability of Greenhouse Gas Emissions From a Subantarctic Peatland Bog

Fine-Scale Spatial Variability of Greenhouse Gas Emissions From a Subantarctic Peatland Bog

Assessment of GHG Interactions in the Vicinity of the Municipal Waste Landfill Site—Case Study

Identifying criteria for greenhouse gas flux estimation with automatic and manual chambers: A case study for N₂O

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Spatial and temporal distribution of methane emissions from a covered landfill equipped with a gas recollection system

Cited by 7 publications

References 41 publications

Fine-Scale Spatial Variability of Greenhouse Gas Emissions From a Subantarctic Peatland Bog

Fine-Scale Spatial Variability of Greenhouse Gas Emissions From a Subantarctic Peatland Bog

Assessment of GHG Interactions in the Vicinity of the Municipal Waste Landfill Site—Case Study

Identifying criteria for greenhouse gas flux estimation with automatic and manual chambers: A case study for N2O

Contact Info

Product

Resources

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Identifying criteria for greenhouse gas flux estimation with automatic and manual chambers: A case study for N₂O