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 1.5°C 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.

Quantification of methane emitted by ruminants: a review of methods.

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.

There is a need to accurately and precisely quantify greenhouse gas (GHG) emissions, specifically methane (CH4), to ensure correct reporting of GHG inventories and, perhaps more importantly, determine how to best mitigate CH4 emissions. The objective of this study was to review existing methods and methodologies to quantify and estimate CH4 emissions from ruminants. Historically, most techniques were developed for specific purposes that may limit their widespread use on commercial farms and for inventory purposes and typically required frequent calibration and equipment maintenance. Whole animal and head respiration chambers, spot sampling techniques, and tracer gas methods can be used to measure enteric CH4 from individual animals, but each technique has its own inherent limitations. The measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the most complex variable creating many uncertainties. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources. Top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point.

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.

The role of the European small ruminant dairy sector in stabilising global temperatures: lessons from GWP* warming-equivalent emission metrics.

Recent calls advocate that a huge reduction in the consumption of animal products (including dairy) is essential to mitigate climate change and stabilise global warming below the 1.5 and 2°C targets. The Paris Agreement states that to stabilise temperatures we must reach a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases (GHG) in the second half of this century. Consequently, many countries have adopted overall GHG reduction targets (e.g. EU, at least 40% by 2030 compared to 1990). However, using conventional metric-equivalent emissions (CO2-e GWP100) as the basis to account for emissions does not result in capturing the effect on atmospheric warming of changing emission rates from short-lived GHG (e.g. methane: CH4), which are the main source of GHG emissions by small ruminants. This shortcoming could be solved by using warming-equivalent emissions (CO2-we, GWP*), which can accurately link annual GHG emission rates to its warming effect in the atmosphere. In our study, using this GWP* methodology and different modelling approaches, we first examined the historical (1990-2018) contribution of European dairy small ruminant systems to additional atmosphere warming levels and then studied different emission target scenarios for 2100. These scenarios allow us to envision the necessary reduction of GHG emissions from Europe's dairy small ruminants to achieve a stable impact on global temperatures, i.e. to be climatically neutral. Our analysis showed that, using this type of approach, the whole European sheep and goat dairy sector seems not to have contributed to additional warming in the period 1990-2018. Considering each subsector separately, increases in dairy goat production has led to some level of additional warming into the atmosphere, but these have been compensated by larger emission reductions in the dairy sheep sector. The estimations of warming for future scenarios suggest that to achieve climate neutrality, understood as not adding additional warming to the atmosphere, modest GHG reductions of sheep and goat GHG would be required (e.g. via feed additives). This reduction would be even lower if potential soil organic carbon (SOC) from associated pastures is considered.

Short- and long-term warming effects of methane may affect the cost-effectiveness of mitigation policies and benefits of low-meat diets.

Methane's short atmospheric life has important implications for the design of global climate change mitigation policies in agriculture. Three different agricultural economic models are used to explore how short- and long-term warming effects of methane can affect the cost-effectiveness of mitigation policies and dietary transitions. Results show that the choice of a particular metric for methane's warming potential is key to determine optimal mitigation options, with metrics based on shorter-term impacts leading to greater overall emission reduction. Also, the promotion of low-meat diets is more effective at reducing greenhouse gas emissions compared to carbon pricing when mitigation policies are based on metrics that reflect methane's long-term behaviour. A combination of stringent mitigation measures and dietary changes could achieve substantial emission reduction levels, helping reverse the contribution of agriculture to global warming.

A systematic review of non-productivity-related animal-based indicators of heat stress resilience in dairy cattle.

INTRODUCTION: Projected temperature rise in the upcoming years due to climate change has increased interest in studying the effects of heat stress in dairy cows. Environmental indices are commonly used for detecting heat stress, but have been used mainly in studies focused on the productivity-related effects of heat stress. The welfare approach involves identifying physiological and behavioural measurements so as to start heat stress mitigation protocols before the appearance of impending severe health or production issues. Therefore, there is growing interest in studying the effects of heat stress on welfare. This systematic review seeks to summarise the animal-based responses to heat stress (physiological and behavioural, excluding productivity) that have been used in scientific literature. METHODS: Using systematic review guidelines set by PRISMA, research articles were identified, screened and summarised based on inclusion criteria for physiology and behaviour, excluding productivity, for animal-based resilience indicators. 129 published articles were reviewed to determine which animal-based indicators for heat stress were most frequently used in dairy cows. RESULTS: The articles considered report at least 212 different animal-based indicators that can be aggregated into body temperature, feeding, physiological response, resting, drinking, grazing and pasture-related behaviour, reactions to heat management and others. The most common physiological animal-based indicators are rectal temperature, respiration rate and dry matter intake, while the most common behavioural indicators are time spent lying, standing and feeding. CONCLUSION: Although body temperature and respiration rate are the animal-based indicators most frequently used to assess heat stress in dairy cattle, when choosing an animal-based indicator for detecting heat stress using scientific literature to establish thresholds, characteristics that influence the scale of the response and the definition of heat stress must be taken into account, e.g. breed, lactation stage, milk yield, system type, climate region, bedding type, diet and cooling management strategies.

Modeling Regional Effects of Climate Change on Soil Organic Carbon in Spain.

Soil organic C (SOC) stock assessments at the regional scale under climate change scenarios are of paramount importance in implementing soil management practices to mitigate climate change. In this study, we estimated the changes in SOC sequestration under climate change conditions in agricultural land in Spain using the RothC model at the regional level. Four Intergovernmental Panel on Climate Change (IPCC) climate change scenarios (CGCM2-A2, CGCM2-B2, ECHAM4-A2, and ECHAM4-B2) were used to simulate SOC changes during the 2010 to 2100 period across a total surface area of 2.33 × 10 km. Although RothC predicted a general increase in SOC stocks by 2100 under all climate change scenarios, these SOC sequestration rates were smaller than those under baseline conditions. Moreover, this SOC response differed among climate change scenarios, and in some situations, some losses of SOC occurred. The greatest losses of C stocks were found mainly in the ECHAM4 (highest temperature rise and precipitation drop) scenarios and for rainfed and certain woody crops (lower C inputs). Under climate change conditions, management practices including no-tillage for rainfed crops and vegetation cover for woody crops were predicted to double and quadruple C sequestration rates, reaching values of 0.47 and 0.35 Mg C ha yr, respectively.

SIMSWASTE-AD - A modelling framework for the environmental assessment of agricultural waste management strategies: Anaerobic digestion.

On-farm anaerobic digestion (AD) has been promoted due to its improved environmental performance, which is based on a number of life cycle assessments (LCA). However, the influence of site-specific conditions and practices on AD performance is rarely captured in LCA studies and the effects on C and N cycles are often overlooked. In this paper, a new model for AD (SIMSWASTE-AD) is described in full and tested against a selection of available measured data. Good agreement between modelled and measured values was obtained, reflecting the model capability to predict biogas production (r2=0.84) and N mineralization (r2=0.85) under a range of substrate mixtures and operational conditions. SIMSWASTE-AD was also used to simulate C and N flows and GHG emissions for a set of scenarios exploring different AD technology levels, feedstock mixtures and climate conditions. The importance of post-digestion emissions and its relationship with the AD performance have been stressed as crucial factors to reduce the net GHG emissions (-75%) but also to enhance digestate fertilizer potential (15%). Gas tight digestate storage with residual biogas collection is highly recommended (especially in temperate to warm climates), as well as those operational conditions that can improve the process efficiency on degrading VS (e.g. thermophilic range, longer hydraulic retention time). Beyond the effects on the manure management stage, SIMSWASTE-AD also aims to help account for potential effects of AD on other stages by providing the C and nutrient flows. While primarily designed to be applied within the SIMSDAIRY modelling framework, it can also interact with other models implemented in integrated approaches. Such system scope assessments are essential for stakeholders and policy makers in order to develop effective strategies for reducing GHG emissions and environmental issues in the agriculture sector.

Gaseous emissions from management of solid waste: a systematic review.

The establishment of sustainable soil waste management practices implies minimizing their environmental losses associated with climate change (greenhouse gases: GHGs) and ecosystems acidification (ammonia: NH3 ). Although a number of management strategies for solid waste management have been investigated to quantify nitrogen (N) and carbon (C) losses in relation to varied environmental and operational conditions, their overall effect is still uncertain. In this context, we have analyzed the current scientific information through a systematic review. We quantified the response of GHG emissions, NH3 emissions, and total N losses to different solid waste management strategies (conventional solid storage, turned composting, forced aerated composting, covering, compaction, addition/substitution of bulking agents and the use of additives). Our study is based on a meta-analysis of 50 research articles involving 304 observations. Our results indicated that improving the structure of the pile (waste or manure heap) via addition or substitution of certain bulking agents significantly reduced nitrous oxide (N2 O) and methane (CH4 ) emissions by 53% and 71%, respectively. Turned composting systems, unlike forced aerated composted systems, showed potential for reducing GHGs (N2 O: 50% and CH4 : 71%). Bulking agents and both composting systems involved a certain degree of pollution swapping as they significantly promoted NH3 emissions by 35%, 54%, and 121% for bulking agents, turned and forced aerated composting, respectively. Strategies based on the restriction of O2 supply, such as covering or compaction, did not show significant effects on reducing GHGs but substantially decreased NH3 emissions by 61% and 54% for covering and compaction, respectively. The use of specific additives significantly reduced NH3 losses by 69%. Our meta-analysis suggested that there is enough evidence to refine future Intergovernmental Panel on Climate Change (IPCC) methodologies from solid waste, especially for solid waste composting practices. More holistic and integrated approaches are therefore required to develop more sustainable solid waste management systems.

Distinguishing sources of N2O in European grasslands by stable isotope analysis.

Nitrifiers and denitrifiers are the main producers of the greenhouse gas nitrous oxide (N(2)O). Knowledge of the respective contributions of each of these microbial groups to N(2)O production is a prerequisite for the development of effective mitigation strategies for N(2)O. Often, the differentiation is made by the use of inhibitors. Measurements of the natural abundance of the stable isotopes of N and O in N(2)O have been suggested as an alternative for the often unreliable inhibition studies. Here, we tested the natural abundance incubation method developed by Tilsner et al.1 with soils from four European grasslands differing in long-term management practices. Emission rates of N(2)O and stable isotope natural abundance of N(2)O and mineral N were measured in four different soil incubations: a control with 60% water-filled pore space (WFPS), a treatment with 60% WFPS and added ammonium (NH(4) (+)) to support nitrifiers, a control with 80% WFPS and a treatment with 80% WFPS and added nitrate (NO(3) (-)) to support denitrifiers. Decreases in NH(4) (+) concentrations, linked with relative (15)N-enrichment of residual NH(4) (+) and production of (15)N-depleted NO(3) (-), showed that nitrification was the main process for mineral N conversions. The N(2)O production, however, was generally dominated by reduction processes, as indicated by the up to 20 times larger N(2)O production under conditions favouring denitrification than under conditions favouring nitrification. Interestingly, the N(2)O concentration in the incubation atmospheres often levelled off or even decreased, accompanied by increases in delta(15)N and delta(18)O values of N(2)O. This points to uptake and further reduction of N(2)O to N(2), even under conditions with small concentrations of N(2)O in the atmosphere. The measurements of the natural abundances of (15)N and (18)O proved to be a valuable integral part of the natural abundance incubation method. Without these measurements, nitrification would not have been identified as essential for mineral N conversions and N(2)O consumption could not have been detected.

Dicyandiamide and 3,4-dimethyl pyrazole phosphate decrease N2O emissions from grassland but dicyandiamide produces deleterious effects in clover.

The application of nitrogen fertilisers leads to different ecological problems such as nitrate leaching and the release of nitrogenous gases. N2O is a gas involved in global warming, therefore, agricultural soils can be regarded as a source of global warming. Soil N2O production comes from both the nitrification and denitrification processes. From an ecological viewpoint, using nitrification inhibitors with ammonium based fertilisers may be a potential management strategy to lower the fluxes of N2O, thus decreasing its undesirable effect. In this study, the nitrification inhibitors (NIs) dicyandiamide (DCD) and 3,4-dimethyl pyrazole phosphate (DMPP) have been evaluated as management tools to mitigate N2O emissions from mineral fertilisation and slurry application in grassland systems (experiments 1 and 2), and to assess the phytotoxic effect of these inhibitors per se on clover (experiment 3). Both nitrification inhibitors acted in maintaining soil nitrogen (N) in ammonium form, decreasing cumulative N2O emissions. DCD, but not DMPP, produced phytotoxic effects and yield reduction in white clover. A nutrient imbalance, which led to a senescence process visually observed as chlorosis and necrosis at the border of the leaves, was noted.