Queue Management Project: Testing Strategies Using the Model.

This Working Paper is one of a series representing work under an SERC grant on queue management strategies for urban traffic control systems whose objectives are:- (i)to generalise the strategies developed in an earlier study of queue management, (ii)to develop a computer graphics based representation of queue propagation and management; (iii)to test the strategies' applicability and performance in UK networks; (iv)to investigate their incorporation into standard signal optimisation programs. Clark (1991) in WP 343 describes the graphics model developed at ITS as a queue-management tool for traffic engineers. In order to calibrate the model, and later implement a suitable queue management strategy recommended by the model, a small oversaturated urban traffic network was required. Six possible sites in the West Yorkshire region were suggested by HETS (West Yorkshire Highway Engineering and Technical Services) for consideration. Wellington Street in Leeds city centre was identified as the most suitable being a linked series of three signalized junctions where blocking-back was commonplace, parking violations were minimal and an adequate filming position was available

Modelling spatial and inter-annual variations of nitrous oxide emissions from UK cropland and grasslands using DailyDayCent

This work contributes to the Defra funded projects AC0116: ‘Improving the nitrous oxide inventory’, and AC0114: ‘Data Synthesis, Management and Modelling’. Funding for this work was provided by the UK Department for Environment, Food and Rural Affairs (Defra) AC0116 and AC0114, the Department of Agriculture, Environment and Rural Affairs for Northern Ireland, the Scottish Government and the Welsh Government. Rothamsted Research receives strategic funding from the Biotechnology and Biological Sciences Research Council. This study also contributes to the projects: N-Circle (BB/N013484/1), U-GRASS (NE/M016900/1) and GREENHOUSE (NE/K002589/1).Peer reviewedPublisher PD

Grain legume production and use in European agricultural systems

ISBN(print) 978-0-12-812419-2; Editor DL SparksThere is a great demand for high-protein materials for livestock feed in Europe and European agriculture has a deficit of about 70% high-protein materials of which 87% is met by imported soybean and soy meal. This reflects the fact that grain legumes are currently under represented in European agriculture and produced on only 1.5% of the arable land in Europe compared with 14.5%on aworldwide basis. Several grain legumes have the potential to replace at least some of the soya currently used in the diets of monogastric animals, ruminants, and fish. There are also opportunities for greater use of legumes in new foods. Here we review the contribution of ecosystem services by grain legumes in European agriculture startingwith provisioningservices in termsof food and feed and moving on to the contribution theymake to both regulating and supporting serviceswhich are in part due to the diversity which these crops bring to cropping systems. We explore the need to understand grain legume production on the time scale of a rotation rather than a cropping season in order to value and manage the agronomic challenges of weed, pests, and diseases alongside themaintenance or improvement of soil structure, soil organic matter, and nutrient cycling. A review of policy interventions to support grain legumes reveals that until very recently these have failed to make a difference in Europe. We contrast the European picture with the interventions that have allowed the development of grain legume production in both Canada and Australia. Whether farmers choose to grow more legumes will depend on market opportunities, the development of supply chains, and policy support aswell as technicalimprovementsof grainlegumeproductionsuchas breeding of new varieties and management development to improve yield stability. However, to really increase the production of grain legumes in Europe, the issues are far more wide reaching than agronomy or subsidy and require a fundamental rethinking of value chains to move grain legumes from being niche products to mainstream commodities.Peer reviewe

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

First 20 years of DNDC: Model evolution and GRAMP.

The DNDC (DeNitrification and DeComposition) model was first developed by Li et al. (1992) as a rain event-driven process-orientated simulation model for nitrous oxide, carbon dioxide and nitrogen gas emissions from the agricultural soils in the U.S. Over the last 20 years, the model has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. The Global Research Alliance Modelling Platform (GRAMP) is a UK-led initiative for the establishment of a purposeful and credible web-based platform initially aimed at users of the DNDC model. With the aim of improving the predictions of soil C and N cycling in the context of climate change the objectives of GRAMP are to: 1) to document the existing versions of the DNDC model; 2) to create a family tree of the individual DNDC versions; 3) to provide information on model use and development; and 4) to identify strengths, weaknesses and potential improvements for the model

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

To what extent is climate change adaptation a novel challenge for agricultural modellers?

Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change

Nitrous oxide emissions from European agriculture - An analysis of variability and drivers of emissions from field experiments

Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logården in Sweden, Maulde in Belgium, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Gödöllö in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N₂O-N ha⁻¹ yr⁻¹, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important determinant of emissions, accounting for 15% of the variance (using linear regression) in the data from the arable sites (<i>p</i> < 0.0001), and 77% in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission factors. Variability of N₂O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation

Impact of global warming on beef cattle production cost in Brazil

Global warming is affecting agribusiness in its economic aspects. Therefore, the prediction of the evolution of Brazilian beef cattle production cost was made using the IPCC forecast scenario for global warming. The methodology consisted of two steps: (i) the development of a fuzzy model that estimated the grazing land capacity (RP) decrease risk as a function of the changes in the average total rain index, air temperature and increase in extension of the dry season; and (ii) the design of an algorithm for predicting the decrease in production as function of the RPfuzzy model, that results in the impact in beef cattle productivity, and consequent increase in production costs. Historical environmental data from important producing counties in the Cerrado were organized and a set of fuzzy Gaussian functions were developed, and three possible settings (optimistic, medium and pessimistic) were considered. The decrease in beef cattle productivity was estimated using the losses in production due to the increase in air temperature and vulnerability of pasture capacity. The boundary settings for the total increase of production cost scenario used the number of animals per area of grazing land, the adoption of grain supplement and its future scenario; and the result output function pointed to a threshold within a variation from an increase in production cost of 80% (optimistic) to 160% (pessimistic). Under the optimistic scenario the total cost of Brazilian beef cattle production in the Cerrado became near to US$2.88 kg-1, while in the pessimistic scenario this cost reached US$ 4.16 kg-1, challenging the international competitiveness of this economic segment.O aquecimento global afeta o agronegócio em seus aspectos econômicos. Foi feita previsão daevolução do custo de produção de carne bovina brasileira usando a predição de aquecimento global do IPCC. A metodologia consistiu de duas etapas: (i) o desenvolvimento de modelo fuzzy que estimou o risco de decréscimo da capacidade de pastagens (RP) em função das mudanças no índice pluviométrico total, na temperatura do ar e na extensão da estação de seca; e (ii) o desenvolvimento de um algoritmo para predição do decréscimo da produção em função de um modelo fuzzy de RP que resulte no impacto na produtividade bovina de corte e conseqüente aumento no custo de produção. Foram organizados os dados históricos de fatores ambientais dos municípios importante produção no Cerrado e um conjunto de funções Gaussianas fuzzy foi desenvolvido e três estimativas possíveis (otimista, média e negativa) foram consideradas. O decréscimo na produtividade do gado foi estimado usando as perdas de produção devido ao acréscimo da temperatura bem como da vulnerabilidade da capacidade de pastagem. O estabelecimento dos limites para o cenário do acréscimo do custo de produção usou o número de unidade animal por área de pastagem, a adoção de suplemento de grãos e o cenário de produção futura; e o resultado da função de saída apontou para uma variação do acréscimo do custo de produção de 80% (otimista) até 160% (pessimista). Sob o cenário otimista, o custo total da produção brasileira de carne bovina no Cerrado chega a US$2,88 kg-1, enquanto no cenário pessimista este custo pode atingir US$ 4,16 kg-1, o que pode comprometer a competitividade internacional do setor