Priorities for mitigating greenhouse gas and ammonia emissions to meet UK policy targets

Agriculture is essential for providing food and maintaining food security while concurrently delivering multiple other ecosystem services. However, agricultural systems are generally a net source of greenhouse gases and ammonia. They, therefore, need to substantively contribute to climate change mitigation and net zero ambitions. It is widely acknowledged that there is a need to further reduce and mitigate emissions across sectors, including agriculture to address the climate emergency and emissions gap. This discussion paper outlines a collation of opinions from a range of experts within agricultural research and advisory roles following a greenhouse gas and ammonia emission mitigation workshop held in the UK in March 2022. The meeting identified the top mitigation priorities within the UK’s agricultural sector to achieve reductions in greenhouse gases and ammonia that are compatible with policy targets. In addition, experts provided an overview of what they believe are the key knowledge gaps, future opportunities and co-benefits to mitigation practices as well as indicating the potential barriers to uptake for mitigation scenarios discussed

Greenhouse gas and ammonia emission mitigation priorities for UK policy targets

Acknowledgements Many thanks to the Association of Applied Biologist’s for organising and hosting the ‘Agricultural greenhouse gases and ammonia mitigation: Solutions, challenges, and opportunities’ workshop. This work was supported with funding from the Scottish Government’s Strategic Research Programme (2022-2027, C2-1 SRUC) and BBSRC (BBS/E/C/000I0320 and BBS/E/C/000I0330). We also acknowledge support from UKRI694 BBSRC (United Kingdom Research and Innovation-Biotechnology and Biological Sciences 695 Research Council; United Kingdom) via grants BBS/E/C/000I0320 and BBS/E/C/000I0330. and Rothamsted Research's Science Initiative Catalyst Award (SICA) supported by BBSRC.Peer reviewedPublisher PD

Novel routes towards bioplastics from plants: elucidation of the methylperillate biosynthesis pathway from Salvia dorisiana trichomes

Plants produce a large variety of highly functionalized terpenoids. Functional groups such as partially unsaturated rings and carboxyl groups provide handles to use these compounds as feedstock for biobased commodity chemicals. For instance, methylperillate, a monoterpenoid found in Salvia dorisiana, may be used for this purpose, as it carries both an unsaturated ring and a methylated carboxyl group. The biosynthetic pathway of methylperillate in plants is still unclear. In this work, we identified glandular trichomes from S. dorisiana as the location of biosynthesis and storage of methylperillate. mRNA from purified trichomes was used to identify four genes that can encode the pathway from geranyl diphosphate towards methylperillate. This pathway includes a (–)-limonene synthase (SdLS), a limonene 7-hydroxylase (SdL7H, CYP71A76), and a perillyl alcohol dehydrogenase (SdPOHDH). We also identified a terpene acid methyltransferase, perillic acid O-methyltransferase (SdPAOMT), with homology to salicylic acid OMTs. Transient expression in Nicotiana benthamiana of these four genes, in combination with a geranyl diphosphate synthase to boost precursor formation, resulted in production of methylperillate. This demonstrates the potential of these enzymes for metabolic engineering of a feedstock for biobased commodity chemical

Cyber security fear appeals:unexpectedly complicated

Cyber security researchers are starting to experiment with fear appeals, with a wide variety of designs and reported efficaciousness. This makes it hard to derive recommendations for designing and deploying these interventions. We thus reviewed the wider fear appeal literature to arrive at a set of guidelines to assist cyber security researchers. Our review revealed a degree of dissent about whether or not fear appeals are indeed helpful and advisable. Our review also revealed a wide range of fear appeal experimental designs, in both cyber and other domains, which confirms the need for some standardized guidelines to inform practice in this respect. We propose a protocol for carrying out fear appeal experiments, and we review a sample of cyber security fear appeal studies, via this lens, to provide a snapshot of the current state of play. We hope the proposed experimental protocol will prove helpful to those who wish to engage in future cyber security fear appeal research

Risk for valvular heart disease after treatment for hodgkin lymphoma

Background: Hodgkin lymphoma (HL) survivors are at increased risk for developing valvular heart disease (VHD). We evaluated the determinants of the risk and the radiation dose-response. Methods: A case-control study was nested in a cohort of 1852 five-year HL survivors diagnosed at ages 15 to 41 years and treated between 1965 and 1995. Case patients had VHD of at least moderate severity as their first cardiovascular diagnosis following HL treatment. Control patients were matched to case patients for age, gender, and HL diagnosis date. Treatment and follow-up data were abstracted from medical records. Radiation doses to heart valves were estimated by reconstruction of individual treatments on representative computed tomography datasets. All statistical tests were two-sided. Results: Eighty-nine case patients with VHD were identified (

Ammonia and nitrous oxide emission factors for excreta deposited by livestock and land-applied manure

Manure application to land and deposition of urine and dung by grazing animals are major sources of ammonia (NH3) and nitrous oxide (N2O) emissions. Utilizing data on NH3 and N2O emissions following land-applied manures and excreta deposited during grazing, emission factors (EFs) disaggregated by climate zone were developed and effects of mitigation strategies evaluated. The NH3 data represents emissions from cattle and swine manures in temperate wet climates, while the N2O data includes cattle, sheep and swine manure emissions in temperate wet/dry and tropical wet/dry climates. The NH3 EFs for broadcast cattle solid manure and slurry were 0.03 and 0.24 kg NH3-N kg-1 total N (TN), respectively, while broadcast swine slurry was 0.29. Emissions from both cattle and swine slurry were reduced between 46 and 62% with low emissions application methods. Land application of cattle and swine manure in wet climates had EFs of 0.005 and 0.011 kg N2O-N kg-1 TN, respectively, while in dry climates the EF for cattle manure was 0.0031. The N2O EF for cattle urine and dung in wet climates was 0.0095 and 0.002 kg N2O-N kg-1 TN, respectively, which were three times greater than for dry climates. The N2O EFs for sheep urine and dung in wet climates were 0.0043 and 0.0005, respectively. The use of nitrification inhibitors reduced emissions in swine manure, cattle urine/dung and sheep urine by 45 to 63%. These enhanced EFs can improve national inventories; however, more data is needed across multiple livestock species and climates

DataMan: A global dataset of nitrous oxide and ammonia emission factors for excreta deposited by livestock and land-applied manure

Nitrous oxide (N2O), ammonia (NH3) and methane (CH4) emissions from the manure management chain of livestock production systems are important contributors to greenhouse gases (GHG) and NH3 emitted by human activities. Several studies have evaluated manure-related emissions and associated key variables at regional, national or continental scales. However, there have been few studies focusing on these emissions using a global dataset. An international project was created (DataMan) to develop a global database on GHG and NH3 emissions from the manure management chain (housing, storage and field), to identify key variables influencing emissions, and ultimately to refine EFs for future national GHG inventories and NH3 emission reporting. This paper describes the “field” database that focuses on N2O and NH3 EFs from land-applied manure and excreta deposited by grazing livestock. We collated relevant information (EFs, manure characteristics, soil properties and climatic conditions) from published peer-reviewed research, theses, conference papers and existing databases. The database, containing 5,632 observations compiled from 184 studies, was relatively evenly split between N2O and NH3 (56% and 44% of the EF values, respectively). The N2O data were derived from studies conducted in 21 countries on five continents, with New Zealand, the UK, Kenya and Brazil representing 86% of the data. The NH3 data originated from studies conducted in 17 countries on four continents, with the UK, Denmark, Canada and the Netherlands representing 79% of the data. Wet temperate climates represented 90% of the total database. The DataMan field database is available online at http:// dataman.azurewebsites.net

DEXi-Dairy: an ex post multicriteria tool to assess the sustainability of dairy production systems in various European regions

Growing awareness of global challenges and increasing pressures on the farming sector, including the urgent requirement to rapidly cut greenhouse gases (GHG) emissions, emphasize the need for sustainable production, which is particularly relevant for dairy production systems. Comparing dairy production systems across the three sustainability dimensions is a considerable challenge, notably due to the heterogeneity of production conditions in Europe. To overcome this, we developed an ex post multicriteria assessment tool that adopts a holistic approach across the three sustainability dimensions. This tool is based on the DEXi framework, which associates a hierarchical decision model with an expert perspective and follows a tree shaped structure; thus, we called it the DEXi-Dairy tool. For each dimension of sustainability, qualitative attributes were defined and organized in themes, sub-themes, and indicators. Their choice was guided by three objectives: (i) better describe main challenges faced by European dairy production systems, (ii) point out synergies and trade-offs across sustainability dimensions, and (iii) contribute to the identification of GHG mitigation strategies at the farm level. Qualitative scales for each theme, sub-theme, and indicator were defined together with weighting factors used to aggregate each level of the tree. Based on selected indicators, a list of farm data requirements was developed to populate the sustainability tree. The model was then tested on seven case study farms distributed across Europe. DEXi-Dairy presents a qualitative method that allows for the comparison of different inputs and the evaluation of the three sustainability dimensions in an integrated manner. By assessing synergies and trade-offs across sustainability dimensions, DEXi-Dairy is able to reflect the heterogeneity of dairy production systems. Results indicate that, while trade-offs occasionally exist among respective selected sub-themes, certain farming systems tend to achieve a higher sustainability score than others and hence could serve as benchmarks for further analyses