Retrospective and projected warming-equivalent emissions from global livestock and cattle calculated with an alternative climate metric denoted GWP

Limiting warming by the end of the century to 1.5̊C compared to pre-Industrial times requires reaching and sustaining net zero global carbon dioxide (CO2) emissions and declining radiative forcing from non-CO2 greenhouse gas (GHG) sources such as methane (CH4). This implies eliminating CO2 emissions or balancing them with removals while mitigating CH4 emissions to reduce their radiative forcing over time. The global cattle sector (including Buffalo) mainly emits CH4 and N2O and will benefit from understanding the extent and speed of CH4 reductions necessary to align its mitigation ambitions with global temperature goals. This study explores the utility of an alternative usage of global warming potentials (GWP*) in combination with the Transient Climate Response to cumulative carbon Emissions (TCRE) to compare retrospective and projected climate impacts of global livestock emission pathways with other sectors (e.g. fossil fuel and land use change). To illustrate this, we estimated the amount and fraction of total warming attributable to direct CH4 livestock emissions from 1750 to 2019 using existing emissions datasets and projected their contributions to future warming under three historical and three future emission scenarios. These historical and projected estimates were transformed into cumulative CO2 equivalent (GWP100) and warming equivalent (GWP*) emissions that were multiplied by a TCRE coefficient to express induced warming as globally averaged surface temperature change. In general, temperature change estimates from this study are comparable to those obtained from other climate models. Sustained annual reductions in CH4 emissions of 0.32% by the global cattle sector would stabilize their future effect on global temperature while greater reductions would reverse historical past contributions to global warming by the sector in a similar fashion to increasing C sinks. The extent and speed with which CH4 mitigation interventions are introduced by the sector will determine the peak temperature achieved in the path to net-zero GHG. © 2023 del Prado et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The authors of this paper report the following sources of funding: Global Dairy Platform supported authors AdP and BL. Ikerbasque, Basque Foundation for Science supported AdP, Spanish National Plan for Scientific and Technical Research and Innovation supported AdP through grant (RYC-2017-22143), Ministerio de Ciencia e Innovación supported AdP through grant (CEX2021-001201-M), Eusko Jaurlaritza supported AdP through grant (BERC 2022-2024), Dairy Management Inc (US) supported AdP and JT through Global Dairy Platform AdP was also supported through Global Dairy Platform by Arla Foods, Dairy Australia, Dairy Companies of New Zealand, Global Round Table for Sustainable Beef, Innovation Centre for US Dairy, McDonalds Corporation, and Meat and Livestock Australia. BL is supported by Global Dairy Platform. JT received salary from Dairy Management Inc. The funders had a role in the study design by providing some of the general questions. The specific roles of these authors are articulated in the ‘author contributions’ section. Many thanks to Arla Foods, Dairy Australia, Dairy Companies of New Zealand, Dairy Man- agement Inc., Global Dairy Platform, Global Round Table for Sustainable Beef, McDonalds Corporation, and Meat and Livestock Australia for helping on the study design and providing some of the general questions

An application of chance-constrained model predictive control to inventory management in hospitalary pharmacy

Trabajo presentado a la 53rd IEEE Conference on Decision and Control (CDC 2014), celebrada del 15 al 17 de diciembre en Los Angeles, California (US).-- et al.Inventory management is one of the main tasks that the pharmacy department has to carry out in a hospital. It is a complex problem that requires to establish a tradeoff between different and contradictory optimization criteria. The complexity of the problem is increased due to the constraints that naturally arise in this type of applications. In this paper, which corresponds to preliminary works performed to implement advanced control techniques for pharmacy management in two Spanish hospitals, we propose and assess chance-constrained model predictive control (CC-MPC) as a mean to relieve this issue.The authors would like to acknowledge Junta de Andalucía (Pharmacon-trol Project, P12-TIC-2400), for funding this work.Peer Reviewe

Increasing Competitiveness through the Implementation of Lean Management in Healthcare

The main aim of this paper was two-fold: first, to design a participative methodology that facilitates lean management implementation in healthcare by adopting the action research approach; second, to illustrate the usefulness of this methodology by applying it to the sleep unit of a public hospital in Spain. This methodology proposes the implementation of lean management in its broadest sense: adopting both lean principles and some of its practical tools or practices in order to achieve competitive advantage. The complete service value chain was considered when introducing changes through lean management implementation. This implementation involved training and involving staff in the project (personnel pillar), detecting and analysing "waste" in value chain processes (processes pillar) and establishing control and measurement mechanisms in line with objectives (key performance indicators pillar) and putting in place improvement actions to achieve these objectives. The application of this methodology brought about an improvement in the management of patient flow in terms of effectiveness, efficiency and quality but also an internal transformation towards lean culture

Estimating soil organic carbon changes in managed temperate moist grasslands with RothC

Temperate grassland soils store significant amounts of carbon (C). Estimating how much livestock grazing and manuring can influence grassland soil organic carbon (SOC) is key to improve greenhouse gas grassland budgets. The Rothamsted Carbon (RothC) model, although originally developed and parameterized to model the turnover of organic C in arable topsoil, has been widely used, with varied success, to estimate SOC changes in grassland under different climates, soils, and management conditions. In this paper, we hypothesise that RothC-based SOC predictions in managed grasslands under temperate moist climatic conditions can be improved by incorporating small modifications to the model based on existing field data from diverse experimental locations in Europe. For this, we described and evaluated changes at the level of: (1) the soil water function of RothC, (2) entry pools accounting for the degradability of the exogenous organic matter (EOM) applied (e.g., ruminant excreta), (3) the month-on-month change in the quality of C inputs coming from plant residues (i.e above-, below-ground plant residue and rhizodeposits), and (4) the livestock trampling effect (i.e., poaching damage) as a common problem in areas with higher annual precipitation. In order to evaluate the potential utility of these changes, we performed a simple sensitivity analysis and tested the model predictions against averaged data from four grassland experiments in Europe. Our evaluation showed that the default model''s performance was 78% and whereas some of the modifications seemed to improve RothC SOC predictions (model performance of 95% and 86% for soil water function and plant residues, respectively), others did not lead to any/or almost any improvement (model performance of 80 and 46% for the change in the C input quality and livestock trampling, respectively). We concluded that, whereas adding more complexity to the RothC model by adding the livestock trampling would actually not improve the model, adding the modified soil water function and plant residue components, and at a lesser extent residues quality, could improve predictability of the RothC in managed grasslands under temperate moist climatic conditions. © 2021 Jebari et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Hematoma epidural cervical tras latigazo cervical

Se describe un hematoma epidural a nivel cervical en un varón de 43 años, tras un traumatismo menor tipo latigazo cervical. Su sintomatología inicial obligó a descartar patología cardiaca llegándose al diagnóstico tras estudio mediante resonancia nuclear magnética. El cuadro clínico parcial y no progresivo desaconsejó la cirugía, observándose su reabsorción con nuevo control de resonancia. Se realza una revisión de la bibliografía, señalándose las principales características de esta entidad poco frecuente.We repor a case of cervical epidural hematoma in a 43 year-old man, after soft-tissue cervical spine strain (known as a “whiplast”). At the beginnig, because previous presumptive cardiac pain in this patient, we need to discart cardiac cause. We made the diagnostic of cervical epidural hematoma with the use of magnetic resonance imaging. The incomplete, not severe and nonprogressing defficits led us to conservative treatment; and the hematoma resolved spontaneously, as documented with a new magnetic resonance imaging. The medical literature relating to this uncommon entity has been reviewe

Animal board invited review: Opportunities and challenges in using GWP* to report the impact of ruminant livestock on global temperature change

Ruminant livestock is a large contributor of CH4 emissions globally. Assessing how this CH4 and other greenhouse gases (GHG) from livestock contribute to anthropogenic climate change is key to understanding their role in achieving any temperature targets. The climate impacts of livestock, as well as other sectors or products/services, are generally expressed as CO2-equivalents using 100-year Global Warming Potentials (GWP100). However, the GWP100 cannot be used to translate emission pathways of short-lived climate pollutants (SLCPs) emissions to their temperature outcomes. A key limitation of handling long- and short-lived gases in the same manner is revealed in the context of any potential temperature stabilisation goals: to achieve this outcome, emissions of long-lived gases must decline to net-zero, but this is not the case for SLCPs. A recent alternative metric, GWP* (so-called ‘GWP-star’), has been proposed to overcome these concerns. GWP* allows for simple appraisals of warming over time for emission series of different GHGs that may not be obvious if using pulse-emission metrics (i.e. GWP100). In this article, we explore some of the strengths and limitations of GWP* for reporting the contribution of ruminant livestock systems to global temperature change. A number of case studies are used to illustrate the potential use of the GWP* metric to, for example, understand the current contribution of different ruminant livestock production systems to global warming, appraise how different production systems or mitigations compare (having a temporal element), and seeing how possible emission pathways driven by changes in production, emissions intensity and gas composition show different impacts over time. We suggest that for some contexts, particularly if trying to directly infer contributions to additional warming, GWP* or similar approaches can provide important insight that would not be gained from conventional GWP100 reporting. © 2023This research is supported by María de Maeztu excellence accreditation 2018-2022 (Ref. MDM-2017-0714), funded by MCIN/AEI/10.13039/501100011033/; and by the Basque Government through the BERC 2022-2025 program. Agustin del Prado is financed by the programme Ramon y Cajal from the Spanish Ministry of Economy, Industry and Competitiveness (RYC-2017-22143) and Ikerbasque. JL acknowledges funding from Wellcome Trust, Our Planet Our Health (Livestock, Environment and People—LEAP), award number 205212/Z/16/Z. FM and SH are funded by the California Air Resources Board (CARB35C10_18ISD025

Spectral and Localization Properties for the One-Dimensional Bernoulli Discrete Dirac Operator

A 1D Dirac tight-binding model is considered and it is shown that its nonrelativistic limit is the 1D discrete Schr?odinger model. For random Bernoulli potentials taking two values (without correlations), for typical realizations and for all values of the mass, it is shown that its spectrum is pure point, whereas the zero mass case presents dynamical delocalization for specific values of the energy. The massive case presents dynamical localization (excluding some particular values of the energy). Finally, for general potentials the dynamical moments for distinct masses are compared, especially the massless and massive Bernoulli cases.Comment: no figure; 24 pages; to appear in Journal of Mathematical Physic

Modeling GHG emissions, N and C dynamics in Spanish agricultural soils.

To date, only few initiatives have been carried out in Spain in order to use mathematical models (e.g. DNDC, DayCent, FASSET y SIMSNIC) to estimate nitrogen (N) and carbon (C) dynamics as well as greenhouse gases (GHG) in Spanish agrosystems. Modeling at this level may allow to gain insight on both the complex relationships between biological and physicochemical processes, controlling the processes leading to GHG production and consumption in soils (e.g. nitrification, denitrification, decomposing, etc.), and the interactions between C and N cycles within the different components of the continuum plant-soil-environment. Additionally, these models can simulate the processes behind production, consumition and transport of GHG (e.g. nitrous oxide, N2O, and carbon dioxide, CO2) in the short and medium term and at different scales. Other sources of potential pollution from soils can be identified and quantified using these process-based models (e.g. NO3 y NH3)