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Beatrice Mandelli

Publications and source records attributed to Beatrice Mandelli.

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Application of LHC Gas Recuperation Systems for Methane Emission Control in Livestock Housing

The CH4rLiE (CH4 Livestock Emission) project investigates the technical feasibility of adapting gas recovery systems from high-energy physics to mitigate methane (CH4) emissions in livestock housing. This work presents a proof-of-principle based on the adaptation of CERN's gas recuperation systems for the capture of CH4 at low concentrations. A laboratory-scale prototype was developed to evaluate the performance of various adsorbent materials under realistic conditions, including multi-stage humidity removal and pressurized gas flows. Experimental results obtained with the prototype led to the selection of commercial Z5 zeolite as the primary adsorbent due to its high adsorption capacity and stable regeneration performance through Vacuum Swing Adsorption cycles. The study demonstrates the feasibility of CH4 capture at concentrations down to 0.1%. Furthermore, it was observed that increasing the CH4 partial pressure enhances the adsorption capacity, with tests conducted up to approximately 5 bar. To bridge the gap between laboratory conditions and the representative 10-100 ppm levels found in dairy barn environments, a negative exponential extrapolation was applied to the experimental data. This allowed for the modeling of the adsorption behavior in the ultra-low concentration regime. These results validate the operational principle and provide the necessary parameters for the design of a full-scale system for field installation.

physics.ins-det

Capturing methane in a barn environment: the CH4 Livestock Emission (CH4rLiE) project

The CH4 Livestock Emission (CH4rLiE) project explores the development of a prototype system for capturing methane emissions in barn environments, offering an alternative approach to mitigating greenhouse gas emissions from livestock farming. Methane (CH4), with a global warming potential significantly higher than CO2 (GWP100 = 27), accounts for ~23% of anthropogenic climate impact. In 2021, The Assessment Report 6 of Intergovernmental Panel on Climate Change quantified CH4 livestock emissions in 123 Mt/yr, which, together with substantial N2O and CO2 emissions, contributed with a 12% to global emissions. Unlike strategies focused on altering animal feed, CH4rLiE investigates post-emission capture using porous materials, such as zeolites, to adsorb methane from barn air. The project draws on CERN's experience with gas recovery systems for particle detectors, adapting similar technologies to agricultural settings. Preliminary estimates, based on measured CH4 concentrations (~20 mg/m3) and partial air filtration in a 250-animal barn, suggest a low but detectable recovery potential, subject to validation through simulation and in-situ testing. Prototype development considers the potential for energy-efficient operation - possibly through pressure swing regeneration - and compatibility with existing ventilation infrastructure, though these aspects remain under evaluation. If methane concentrations in barns prove too diluted, the system may be better suited for environments with higher gas levels, such as pigsties or landfills. NH3 capture for fertilizer production is planned as a future enhancement. CH4rLiE aims to assess the feasibility of emission recovery in livestock settings without affecting animal welfare, contributing to sustainable farming practices, resource efficiency, and circular bioeconomy goals.

physics.ins-det

Characterization of the effect of plastic gas pipes with the use of a Single Wire Proportional Chamber

Plastic gas pipes are widely used in experimental setups for gaseous detectors, due to their flexibility and easiness of use. This report describes the characterization studies realized on the use of plastic gas pipes, particularly in relation to the accumulation of impurities in gas systems that they may cause. A laboratory setup has been implemented to evaluate the possible effects caused by plastic pipes, in terms of their specific impact on O2 and H2O accumulation and the consequences on detectors performance. As Single Wire Proportional Chambers are very sensitive to the presence of pollutants and gas mixture variations, this type of detector was chosen to perform the study.

physics.ins-det

Performance and aging studies for the ALICE muon RPCs

The ALICE muon trigger (MTR) system consists of 72 Resistive Plate Chamber (RPC) detectors arranged in two stations, each composed of two planes with 18 RPCs per plane. The detectors are operated in maxi-avalanche mode using a mixture of 89.7% C$_2$H$_2$F$_4$, 10% i-C$_4$H$_{10}$ and 0.3% SF$_6$. A number of detector performance indicators, such as efficiency and dark current, have been monitored over time throughout the LHC Run2 (2015-18). While the efficiency showed very good stability, a steady increase in the absorbed dark current was observed. Since the end of 2018, the LHC has entered a phase of long shutdown, during which the ALICE experiment will be upgraded to cope with the next phase of data taking, expected in 2021. The MTR is undergoing a major upgrade of the front-end and readout electronics, and will change its functionalities, becoming a Muon Identifier. Only the replacement of the most irradiated RPCs is planned during the upgrade. It is therefore important to perform dedicated studies to gain further insights into the status of the detector. In particular, two RPCs were flushed with pure Ar gas for a prolonged period of time and a plasma was created by fully ionizing the gas. The output gas was analyzed using a Gas Chromatograph combined with a Mass Spectrometer and the possible presence of fluorinated compounds originating from the interaction of the plasma with the inner surfaces of the detector has been assessed using an Ion-Selective Electrode station. This contribution will include a detailed review of the ALICE muon RPC performance at the LHC. The procedure and results of the argon plasma test, described above, are also discussed.

physics.ins-det