Feasibility of mitigation measures for agricultural greenhouse gas emissions in the UK. A systematic review.

The UK Government has set an ambitious target of achieving a national "net-zero" greenhouse gas economy by 2050. Agriculture is arguably placed at the heart of achieving net zero, as it plays a unique role as both a producer of GHG emissions and a sector that has the capacity via land use to capture carbon (C) when managed appropriately, thus reducing the concentration of carbon dioxide (CO2) in the atmosphere. Agriculture's importance, particularly in a UK-specific perspective, which is also applicable to many other temperate climate nations globally, is that the majority of land use nationwide is allocated to farming. Here, we present a systematic review based on peer-reviewed literature and relevant "grey" reports to address the question "how can the agricultural sector in the UK reduce, or offset, its direct agricultural emissions at the farm level?" We considered the implications of mitigation measures in terms of food security and import reliance, energy, environmental degradation, and value for money. We identified 52 relevant studies covering major foods produced and consumed in the UK. Our findings indicate that many mitigation measures can indeed contribute to net zero through GHG emissions reduction, offsetting, and bioenergy production, pending their uptake by farmers. While the environmental impacts of mitigation measures were covered well within the reviewed literature, corresponding implications regarding energy, food security, and farmer attitudes towards adoption received scant attention. We also provide an open-access, informative, and comprehensive dataset for agri-environment stakeholders and policymakers to identify the most promising mitigation measures. This research is of critical value to researchers, land managers, and policymakers as an interim guideline resource while more quantitative evidence becomes available through the ongoing lab-, field-, and farm-scale trials which will improve the reliability of agricultural sustainability modelling in the future. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-023-00938-0.

Are single global warming potential impact assessments adequate for carbon footprints of agri-food systems?

The vast majority of agri-food climate-based sustainability analyses use global warming potential (GWP100) as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP100 in Life Cycle Assessments (LCAs), particularly of food systems which generate large amounts of methane (CH4) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions (e.g. Global Temperature Change Potential (GTP)). This paper reports a largescale sensitivity analysis using a pasture-based beef production system (a high producer of CH4 emissions) as an exemplar to compare various climatatic impact assessments: CO2-equivalents using GWP100 and GTP100, and 'CO2-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP100 and GTP100 producing substantially different results due to their different treatments of CH4 in the context of carbon dioxide (CO2) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different greenhouse gas emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.

Response of soil health indicators to dung, urine and mineral fertilizer application in temperate pastures.

Healthy soils are key to sustainability and food security. In temperate grasslands, not many studies have focused on soil health comparisons between contrasting pasture systems under different management strategies and treatment applications (e.g. manures and inorganic fertilisers). The aim of this study was to assess the responses of soil health indicators to dung, urine and inorganic N fertiliser in three temperate swards: permanent pasture not ploughed for at least 20 years (PP), high sugar ryegrass with white clover targeted at 30% coverage reseeded in 2013 (WC), and high sugar ryegrass reseeded in 2014 (HG). This study was conducted on the North Wyke Farm Platform (UK) from April 2017 to October 2017. Soil health indicators including soil organic carbon (SOC, measured by loss of ignition and elemental analyser), dissolved organic carbon (DOC), total nitrogen (TN), C:N ratio, soil C and N bulk isotopes, pH, bulk density (BD), aggregate stability, ergosterol concentration (as a proxy for fungi biomass), and earthworms (abundance, mass and density) were measured and analysed before and after application of dung and N fertilizer, urine and N fertiliser, and only N fertiliser. The highest SOC, TN, DOC, ergosterol concentration and earthworms as well as the lowest BD were found in PP, likely due to the lack of ploughing. Differences among treatments were observed due to the application of dung, resulting in an improvement in chemical indicators of soil health after 50 days of its application. Ergosterol concentration was significantly higher before treatment applications than at the end of the experiment. No changes were detected in BD and aggregate stability after treatment applications. We conclude that not enough time had passed for the soil to recover after the ploughing and reseeding of the permanent pasture, independently of the sward composition (HG or WC). Our results highlight the strong influence of the soil management legacy in temperate pasture and the positive effects of dung application on soil health over the short term. In addition, we point out the relevance of using standardised methods to report soil health indicators and some methodological limitations.

Rethinking efficiency: Growth curves as a proxy for inputs and impacts in finishing beef systems.

Quantifying and improving efficiency within beef systems is essential for economic and environmental sustainability. The industry standard for assessing efficiency is liveweight gain per day, however, this metric is limited in that it values each day of a growing animal's life as equally costly, despite the increasing maintenance requirements, inputs, and emissions associated with increasing liveweight. Quantifying the area under the growth curve (AUC) considers both time and liveweight as a cost and therefore may hold potential as a better estimate of cost, impact, and efficiency in beef systems. Liveweight data was taken from 439 finishing beef cattle split across three herds grazing on different pastures, known as 'farmlets'. Analysis was conducted in three parts: [1] Validation of AUC as a proxy for costs using data from a sub-set of 87 animals that had been part of a previous life cycle assessment (LCA) study in which dry matter intake (DMI), methane emissions (CH4), and nitrous oxide emissions (N2O) were calculated. [2] Calculation of AUC relative to liveweight gain (LWG AUC-1) and comparison of that metric against the industry standard of liveweight gain per day (LWG day-1). [3] Assessment of how LWG AUC-1 varied with breed, sex, and management. When comparing to LCA results, AUC correlated significantly with DMI (r = 0.886), CH4 (r = 0.788) and N2O (r = 0.575) emissions. Over the full dataset, there was a negative non-linear relationship between LWG AUC-1 and slaughter age (r = -0.809). There was a significant difference in LWG AUC-1 between breeds (p = 0.046) and farmlets (p = 0.028), but not sex (p = 0.388). LWG AUC-1 has the potential to act as a proxy for feed intake and emissions. In that regard it is superior to LWG day-1, whilst requiring no additional data. Results highlighted the decreasing efficiency of beef cattle over time and the potential benefits of earlier slaughter. The use of LWG AUC-1 could allow farmers to improve their understanding of efficiency within their herds, aiding informed management decision making.

Data, and sample sources thereof, on water quality life cycle impact assessments pertaining to catchment scale acidification and eutrophication potentials and the benefits of on-farm mitigation strategies.

Based on recent spatially aggregated June Agriculture Survey data and site-specific environmental data, information from common farm types in the East of England was sourced and collated. These data were subsequently used as key inputs to a mechanistic environmental modelling tool, the Catchment Systems Model, which predicts environmental damage arising from various farm types and their management strategies. The Catchment Systems Model, which utilises real-world agricultural productivity data (samples and appropriate consent provided within the Mendeley Data repository) is designed to assess not only losses to nature such as nitrate, phosphate, sediment and ammonia, but also to predict how on-farm intervention strategies may affect environmental performance. The data reported within this article provides readers with a detailed inventory of inputs such as fertiliser, outputs including nutrient losses, and impacts to nature for 1782 different scenarios which cover both arable and livestock farming systems. These 1782 scenarios include baseline (i.e., no interventions), business-as-usual (i.e., interventions already implemented in the study area) and optimised (i.e., best-case scenarios) data. Further, using the life cycle assessment (LCA) methodology, the dataset reports acidification and eutrophication potentials for each scenario under two (eutrophication) and three (acidification) impact assessments to offer an insight into the importance of impact assessment choice. Finally, the dataset also provides its readers with percentage changes from baseline to best-case scenario for each farm type.

Assessing catchment scale water quality of agri-food systems and the scope for reducing unintended consequences using spatial life cycle assessment (LCA).

Life cycle assessment is a multidisciplinary framework usually deployed to appraise the sustainability of various product or service supply-chains. Over recent decades, its use in the agri-food sector has risen sharply, and alongside this, a wide range of methodological advances have been generated. Spatial-life cycle assessment, defined in the current document as the interpretation of life cycle assessment results within a geographical nature, has not gone unexplored entirely, yet its rise as a sub-method of life cycle assessment has been rather slow relative to other avenues of research (e.g., including the nutritional sciences within life cycle assessment). With this relative methodological stagnation as a motivating factor, our paper combines a process-based model, the Catchment Systems Model, with various life cycle impact assessments (ReCiPe, Centre for Environmental Studies and Environmental Product Declaration) to propose a simple, yet effective, approach for visualising the technically feasible efficacy of various on-farm intervention strategies. As water quality was the primary focus of this study, interventions reducing acidification and eutrophication potentials of both arable and livestock farm types in the Southeast of England were considered. The study site is an area with a marked range of agricultural practices in terms of intensity. All impacts to acidification potential and eutrophication potential are reported using a functional unit of 1 ha. Percentage changes relative to baseline farm types, i.e., those without any interventions, arising from various mitigation strategies, are mapped using geographical information systems. This approach demonstrates visually how a spatially-orientated life cycle assessment could provide regional-specific information for farmers and policymakers to guide the restoration of certain waterbodies. A combination of multiple mitigation strategies was found to generate the greatest reductions in pollutant losses to water, but in terms of individual interventions, optimising farm-based machinery (acidification potential) and fertiliser application strategies (eutrophication potential) were found to have notable benefits.

Applications of nutritional functional units in commodity-level life cycle assessment (LCA) of agri-food systems.

PURPOSE: The nutritional quality of final products is attracting an increased level of attention within life cycle assessment (LCA) literature of agri-food systems. The majority of these studies, however, are based on comparisons at the dietary level and, therefore, are unable to offer immediate implications for farmers as to how best to produce food. This article evaluates recent literature examining the nutrition-environment nexus at the commodity level, with the aim to identify potential pathways towards sustainability analysis that can inform both consumers and producers. METHODS: A systematic search of literature was carried out to produce a shortlist of studies, and strict exclusion criteria were applied to them afterwards to eliminate irrelevant material. The studies thus selected were classified into one of three tiers based on the level of complexity with regard to their functional units: (1) based on single nutrients, (2) based on composite indicators derived from multiple nutrients and (3) based on commodity-level analysis in a dietary context. RESULTS AND DISCUSSION: Sixteen papers were identified for inclusion in the review. All of them accounted for climate change either directly or indirectly, whilst only five addressed different impact categories at the same time. Nine studies estimated environmental impacts under functional units associated with nutrient density scores, and the others utilised alternative approaches to account for nutritional value such as linear programming and end-point modelling combined with epidemiological data. A recently developed method to calculate the marginal contribution of a commodity to the overall nutritional value of a specific diet was considered to be a successful first step in bridging the aforementioned knowledge gap. CONCLUSIONS: The LCA community should continue the ongoing effort to link farm management decisions to diet-level environmental impacts through an enhanced focus on human nutrition across the entire value chain. Future research comparing environmental performances of multiple food groups or multiple production systems should acknowledge differences in nutritional composition and bioavailability between the final products and, ideally, the effects of these nutrients on overall dietary quality.

Framework for life cycle assessment of livestock production systems to account for the nutritional quality of final products.

Life cycle assessment (LCA) is widely regarded as a useful tool for comparing the environmental impacts of multiple livestock production systems. While LCA results are typically communicated in the form of environmental burdens per mass unit of the end product, it is increasingly becoming recognized that the product quality also needs to be accounted for to truly understand the value of a farming system to society. To date, a number of studies have examined environmental consequences of different food consumption patterns at the diet level; however, few have addressed nutritional variations of a single commodity attributable to production systems, leaving limited insight into how on-farm practices can be improved to better balance environment and human nutrition. Using data from seven livestock production systems encompassing cattle, sheep, pigs, and poultry, this paper proposes a novel framework to incorporate nutritional value of meat products into livestock LCA. The results of quantitative case studies demonstrate that relative emissions intensities associated with different systems can be dramatically altered when the nutrient content of meat replaces the mass of meat as the functional unit, with cattle systems outperforming pig and poultry systems in some cases. This finding suggests that the performance of livestock systems should be evaluated under a whole supply chain approach, whereby end products originating from different farm management strategies are treated as competing but separate commodities.