A near-field Gaussian plume inversion flux quantification method, applied to unmanned aerial vehicle sampling

The accurate quantification of methane emissions from point sources is required to better quantify emissions for sector-specific reporting and inventory validation. An unmanned aerial vehicle (UAV) serves as a platform to sample plumes near to source. This paper describes a near-field Gaussian plume inversion (NGI) flux technique, adapted for downwind sampling of turbulent plumes, by fitting a plume model to measured flux density in three spatial dimensions. The method was refined and tested using sample data acquired from eight UAV flights, which measured a controlled release of methane gas. Sampling was conducted to a maximum height of 31 m (i.e. above the maximum height of the emission plumes). The method applies a flux inversion to plumes sampled near point sources. To test the method, a series of random walk sampling simulations were used to derive an NGI upper uncertainty bound by quantifying systematic flux bias due to a limited spatial sampling extent typical for short-duration small UAV flights (less than 30 min). The development of the NGI method enables its future use to quantify methane emissions for point sources, facilitating future assessments of emissions from specific source-types and source areas. This allows for atmospheric measurement-based fluxes to be derived using downwind UAV sampling for relatively rapid flux analysis, without the need for access to difficult-to-reach areas

Improving yields from vertical landfill wells through better design, installation and maintenance

A review of published investigations and groundwater well installation practice has established what factors are known to affect the performance of vertical wells: the design and installation of the well, the low hydraulic conductivity of waste and the physical and microbial clogging of the filter pack and well screen.  Down-well CCTV surveys and exhumations have shown that chemical precipitations are also common, often completely coating the well screen and closing all slots, though precipitates were generally only present in the gas zone, above the leachate table, where the closure of slots will not attribute to well losses.  Smearing of ground waste and cover soils around the borehole was observed in exhumed wells drilled using a rotary barrel-auger. Over time, sediments and waste pieces may be washed into the well and will be a function of the flow velocity and the pumping regime.  Accumulations of material will reduce the effective drawdown in the well.  Field trials have demonstrated that removing the material using development techniques has an adverse effect on performance due to the invasion of soils into the filter pack.  When designing new wells for use in a landfill, a compromise may have to be made between a design that limits well losses, a design that prevents fine-grained material from being washed into the well, and one that is not prone to microbial clogging.  Rules used in the groundwater industry for selecting filter packs and well screens, may, therefore, not be suitable for landfill wells, though where sulphate reducing processes are the dominant degradation mechanism, fine-grained filters can be used.  If a well does become clogged with deposited sediments, then well development techniques should be avoided.</p

Supporting data for Single-Well Injection-Withdrawal Tests as a Contaminant Transport Characterisation Tool for Landfilled Waste

This sheet contains the breakthrough curves that are given in Fig. 3 of Rees-White, Woodman, Beaven, Barker and Rollinson, 2021, Waste Management, https://doi.org/10.1016/j.wasman.2021.04.047</span

Dataset for Doublet tracer tests to determine the contaminant flushing properties of a municipal solid waste landfill

Data supporting: Woodman, N., Rees-White, T., Beaven, R., Stringfellow, A., &amp; Barker, J. (2017). Doublet tracer tests to determine the contaminant flushing properties of a municipal solid waste landfill. Journal of Contaminant Hydrology.</span

Direct Measurement of Landfill Emissions using the Tracer Gas Dispersion Method

Methane is a significant greenhouse gas (GHG) with a 100-year global warming potential 28 times that of carbon dioxide. Anaerobic degradation of organic wastes in landfills creates a major source of anthropogenic methane which, when collected, is an important source of renewable energy. However, fugitive emissions of landfill gas are estimated to account for around a third of the total UK emissions of methane.Currently, UK landfill methane emission reporting is based on a national landfill gas generation model (MELMod). Landfill gas collected for energy generation or flaring can be measured, and this is subtracted from the predicted gas generation rate to give the combined amount of fugitive methane emissions and the methane bio-oxidised (to carbon dioxide) in the soils covering the landfill. The ratio of the amount of landfill gas collected to the amount generated is the landfill gas collection efficiency, which is calculated by MELMod. A recent trend in MELMod outputs, where predicted gas generation rates are falling, combined with no drop in the amount of gas collection reported by industry, has started to increase the calculated gas collection rates towards values (around 75%) previously considered unrealistically high. Higher gas collection efficiency rates are to be welcomed, but monitoring of emissions at a selection of landfills would provide evidence for the verification of GHG (MELMod) inventory modelling and allow validate individual site performance.National inventory reporting requires an annual mass of emitted methane. However, techniques for measuring methane emissions provide the emission rate only at the point of measurement. Methane emissions may vary due to a number of factors that include, for example, the season, meteorological conditions and operational controls at the site. Without a better understanding of the factors that influence how representative individual methane emission measurements are, simple extrapolations of such measurements to provide an annual averaged emission rate must be treated with caution.The aim of this research was to quantify the variability in whole site methane emission rates from landfill and to help understand how different operational, meteorological and other site conditions affect these emission rates.The method used to measure whole site methane emissions was the tracer gas dispersion method (TDM). The technique involves the controlled and measured release of a tracer gas (acetylene) from the landfill. Methane and acetylene gas concentrations are then measured downwind of the landfill using a mobile analytical instrument to obtain concentration values across the gas plume. TDM is based on the assumption that the tracer gas released at an emission source will disperse in the atmosphere in the same way as methane emitted from the landfill. The method is well-established internationally and considerable work has been undertaken to help understand the potential errors associated with the method (within approximately ±20%).Three landfills (one closed and restored, Site A; and two operational, Sites B and C) were surveyed under different meteorological and operational conditions using the TDM

Towards a more rational approach for the design of cement-bentonite grouts

Cement-bentonite grouts are commonly used to seal boreholes containing different types of geotechnical instrumentation. The function and type of instrumentation and the surrounding ground conditions dictate the desired engineering properties of the grout, including strength, stiffness and permeability. Cement-bentonite grouts have been little studied, and there is not much guidance from which to determine the proportion of constituents (cement/bentonite and water) to obtain particular engineering properties in the final grout. This makes it desirable to try to mix or test grouts in the laboratory prior to deployment on site, but it can be difficult to know where to start. Further difficulties arise from the tendency to mix cement-bentonite grouts in small batches on site, where the water chemistry, the type and form of bentonite, and mixing apparatus may vary. The paper presents a brief summary of current understanding, and then looks at range of existing grout mixes and their engineering properties to propose an interaction diagram to try to suggest possible mixing and final set properties of grouts based on the proportion of constituents used (cement, bentonite and water). The diagram has some limitations, not least a lack of quantitative data to support some aspects, but the authors hope that it could form a rational basis that can be further developed

Vertical heterogeneity of chromium as a proxy for reactive metallic contaminants in the pore water of a municipal solid waste landfill subject to leachate recirculation

As part of the experiment introduction sustainable landfill management (iDS), three pilot projects were instigated in which landfills are being stabilized through leachate recirculation and/or aeration. The ultimate goal of these projects is to improve the leachate quality until it complies with previously derived environmental protection criteria. The hydrology and leachate transport of one of the three landfills – a municipal solid waste landfill being subjected to leachate recirculation - has been difficult to characterize. To further elucidate transport processes in this landfill, two vadose zone monitoring systems (VMS) have been installed. The VMS are installed at a 45 degree incline, and allow for pore water sampling at 0.4 metre depth intervals between 3 – 6.5 metres and 9.6 – 13 metres below the landfill surface. These systems provide a unique opportunity to collect and analyse in-situ pore water samples for a multitude of parameters of importance for contaminant speciation and transport, thereby providing valuable information on the vertical heterogeneity within the landfill. Starting from July 2022, the VMS are sampled every 3 months and analysed for parameters relevant for understanding contaminant availability and transport throughout the landfill, i.e. contaminant concentrations, concentrations of reactive colloidal particles, pH, and electrical conductivity. A separate paper focuses on the amount and composition of dissolved organic matter in the pore water as a function of depth in the landfill. This paper builds further on that study and describes how these parameters ultimately govern the speciation and vertical distribution of contaminants and its change with time, using Chromium as a proxy for contaminant behaviour

Summary data for tracer gas dispersion tests for landfill methane emission monitoring at a UK landfill

This dataset supports the publications: 1) Rees-White, T. C., M&oslash;nster, J., Beaven R. P., Scheutz, C. (2018) Measuring methane emissions from a UK landfill sing the tracer dispersion method and the influence of operational and environmental factors https://doi.org/10.1016/j.wasman.2018.03.023 2) Matacchiera F, Manes C, Beaven RP, Rees-White TC, Boano F, M&oslash;nster J and Scheutz C (2018). AERMOD as a Gaussian dispersion model for planning tracer gas dispersion tests for landfill methane emission quantification https://doi.org/10.1016/j.wasman.2018.02.007 Contents +++++++++ This dataset contains the data discussed within the papers listed above and in certain Figures from the Rees-White paper. The figures are as follows: Fig. 3. Atmospheric pressure and wind speed during the period of August 5th to August 14th, 2014. Start and end times of each TDM experiment are given as vertical lines Fig. 4. Incoming solar radiation and air temperature during the period of August 3th to August 14th, 2014. Start and end times of each TDM experiment are given as vertical lines Fig. 6 (a to f). Methane emission data for each transect in a TDM with average overall emission and the 95% confidence interval. The name of the monitoring route used for a given transect is also shown Fig. 7. Measured methane emissions vs. average wind speed for the six TDM trials. Linear regression is given (R2 = -0.82). Fig. 8. Individual transect data from TDM2 shown against estimated wind speed, interpolated between measurement points. Data are colour coded to reflect the monitoring route used. a) shows data between 18:07 and 20:09, and b) 20:59 to 22:14. Fig. 9. a) Average methane emission data from each monitoring route shown against measuring distance, b) Average methane emission rate from each monitoring route for a given TDM measured at different monitoring distances. Geographic location of this data collection: University of Southampton, U.K. Dataset available under a CC BY 4.0 licence Publisher: University of Southampton, U.K. Date: April 2018</span