Modelling uncertainty for decision making on ammonia mitigation with trees in the landscape (MUDMAT).

Lead Research Organisation: UK Ctr for Ecology & Hydrology fr 011219
Department Name: Atmospheric Chemistry and Effects


In the agricultural landscape there are competing needs of making the best economical use of the land for food production and the use of land to mitigate against Nitrogen pollution from agriculture. Agricultural practises accounts for over 80% of ammonia emissions within the UK with releases from livestock housing and manure management through storage and spreading. Deposition of nitrogen in the form of ammonia can cause eutrophication and acidification effects on semi-natural ecosystems, leading to species composition changes and reduced biodiversity. The Clean Air Strategy 2019 has given significant focus to the impact of ammonia emissions and the subsequent atmospheric nitrogen load on ecosystems together with the particulate form of ammonia affecting human health outcomes. Over 60% of the UK's semi-natural habitats exceed their environmental limit for nitrogen deposition. Mitigation measures have been proposed by Government to support farmers in providing reductions in ammonia emissions. One effective abatement strategy is to plant tree shelter-belts downwind of livestock housing and slurry stores to 'scavenge' ammonia. (10-25% Bealey et al. 2014). Trees are particularly effective scavengers of air pollutants due to their effect on turbulence. Because of their rougher surface and high surface area trees are particularly effective scavengers of air pollutants.
Recently a decision support tool has been created to help land managers quickly predict the potential of tree planting to mitigate in ammonia pollution based on simple user input choices. This web-based decision tool can help resolve the competing interests of using agricultural land for food production and pollution mitigation, by allowing the land manager to assess tree planting strategies that maximise ammonia abatement for the minimum use of land. Therefore, the web tool has proved to be very popular with key food producers (e.g. egg industry), and agricultural decision makers notably pollution regulators, conservation bodies and also planners.
However there is no quantification of the reliability of the predictions made from the web tool. This is a key omission and hampers its use in decision making. Since models are never perfect representations of the landscape, model predictions are only as good as the quantification of how certain those predictions are. Compounding this, in the web tool, the computationally expensive coupled turbulence-deposition model MODDAAS-THETIS is replaced with a very simple empirical model and there is at present no way of quantifying the reduced accuracy of predictions associated with this simplification.
Here we propose to use statistical methods to create a faster but quantifiably traceable emulator of MODDAAS-THETIS which will replace the empirical model in the web tool and will also allow uncertainty of the predictions from MODDAAS-THETIS to be quantified through the emulator.

Our key objectives are to:
1) Provide a decision tool that will help land managers to make the most economically efficient use of the agricultural land whilst minimising ammonia pollution.
2) Make a step-change improvement in decision making concerning the mitigation of ammonia pollution in the landscape by bringing state-of-the-art statistical methods to a web-based decision analysis system by quantifying the uncertainty of the predictions made.
3) Significantly improve the model behind the web-based tool making it traceable statistically to the underlying process-based model (MODDAAS-THETIS) through emulation and increasing the tree belt planting options available to the decision makers for predicting the mitigation of ammonia in the tool.
4) Establish a methodology for emulating the multivariate spatial and temporal output from pollution transport models in the landscape making it possible to quantify uncertainty in the predictions from these computationally-expensive models.

Planned Impact

Ammonia is spatially very heterogeneous in the landscape with concentrations going up and down as the patchwork of agricultural practices emit at varying levels. At the same time the rural landscape is inter-twined with many protected habitat site networks resulting in a conflict of interests between food production and protecting sensitive habitats. Making landscape decisions around these hot-spots of ammonia to provide the optimal mitigation options is challenging. These decisions are complex and involve wide stakeholder group involvement. The outcomes of the MUDMAT project will provide a reliable tool for a variety of stakeholders to be able to make confident decisions in the planning and design for planting trees for ammonia mitigation around e.g. existing livestock sheds or new installations. Beneficiaries of the project outputs will be:
1. Farmers and Woodland and Farm Advisors - across the UK, tree planting around poultry housing for welfare purposes has been adopted by hundreds of farms, driven by food industry, charities such as the Woodland Trust, and consumers - with great success. In addition to welfare benefits, these farmers are now appreciating the added benefit of the trees being able to 'soak-up' ammonia emitted from their poultry sheds and fulfil their commitment to reducing ammonia emissions. The current tool has been trialled and demoed by farmers and it is seen as an extremely beneficial tool to the industry in being able to demonstrate ammonia reductions and to be confident in those reduction numbers. Greater confidence in the predictions from MUDMAT would open up new opportunities for encouraging further planting, not only within the egg-producing sector but also across all aspects of livestock and dairy production.
2. Pollution Regulators, Conservation Agencies & Policy Implementers - a key aim of the Landscape Decisions SFP is to address how we can manage land better for the benefit of society as a whole including the environment, and to provide real world solutions that can make this difference. This includes supporting cross-departmental decisions at the policy level and in practice to deliver sustainably produced food and environmental public goods.
Regulators and Conservation officers play a key role in the decision making for the permitting of intensive farming practises. This involves the underseeing of application for new of expanding livestock installations. A holistic approach is now undertaken and best practice and ammonia reducing measures are required. There has been wide interest in the use of planting trees around livestock sheds and slurry stores as a complimentary measure to reduce emissions and this tool can aid spatial planning of ammonia emitting practices on the farm. This type of activity comes under the Industrial Emissions Directive (IED 2010/75/EU), e.g. for large pig and poultry farms, and also as part of the Code of Good Agricultural Practice (COGAP) for Reducing Ammonia Emissions which has been developed to support farmers with practical steps to reduce their ammonia emissions and improve their nitrogen use efficiency. For conservation agencies like Natural England it incorporates remedies for building ecological resilience as described in their Conservation Strategy for the 21st Century.
3. Local Authority Planners/Landscape Planners - planning forms the main control on expanding agricultural practices in the landscape; more and more applications are passing though planning departments that concern the release of ammonia. In particular, this includes the expansion of poultry installations. For example, in Shropshire the council has seen a large increase in applications for the building of new poultry sheds and they have indicated a strong interest in the use of trees to mitigate against ammonia. The ammonia reduction tool would be key part of their tool-kit in predicting what the trees can capture, in term of ammonia, and where such installations can be built.


10 25 50

Related Projects

Project Reference Relationship Related To Start End Award Value
NE/T004185/1 25/09/2019 30/11/2019 £62,217
NE/T004185/2 Transfer NE/T004185/1 01/12/2019 31/12/2020 £46,663
Description Over 60% of the UK's semi-natural habitats exceed threshold limits where damage (species composition changes and reduced biodiversity) is caused by nitrogen. Agricultural practices account for over 80% of nitrogen emissions, in the form of ammonia (NH3), within the UK. Government guidance supports farmers to reduce their ammonia emissions including mitigation options like planting tree shelter-belts to 'scavenge', that is, deposit, ammonia. Farmers need tools to help them quantify how options for planting tree shelter-belts will influence their NH3 pollution.

Our aim in this project was to improve decision making concerning the mitigation of ammonia pollution in the landscape by making a step-change improvement to a pre-existing web-based decision tool.

The pre-existing web-tool was popular with farmers but had two main weaknesses.
1.) The tool relied on a very simple empirical model to make ammonia abatement predictions. This model had been quick to create and demonstrated a "proof of concept" of the tool but it was unlikely to give accurate predictions.
2.) Related to this there was no pre-existing way to assess the accuracy of the predictions from the simple empirical model and hence the tool could not give the farmers an indication of the reliability of the predictions made.

The consequence of these weaknesses was that we were unable to recommend the decision tool to farmers and other decision makers as a basis for them making important and potentially costly decisions.

Previous work (Bealey et al 2014) had demonstrated that the model MODDAAS had skill in predicting the effect of tree shelter-belts on capturing ammonia so our first objective was to make an explicit link from the web-tool to this model. The MODDAAS model when run on a normal PC was many times more expensive to run than the simple empirical model used in the web-tool. So we initially thought that we would be forced into emulating MODDAAS to make it practical for the web-tool. Emulators are an approximation of the original model but have the advantage of quantifying the uncertainty introduced in making that approximation. Porting OpenFOAM/MODDAAS to the CEDA data intensive supercomputer JASMIN ( decreased the run time of the model considerably. We realised that, by leveraging the parallel computing power of the LOTUS cluster on JASMIN and storing the results of OpenFOAM/ MODDAAS in a database, we could link the web-tool to MODDAAS directly avoiding the need for emulation; an obvious advantage.

Our second objective was to add information on the reliability of the predictions from the decision tool. We did this by making an uncertainty analysis (UA) of MODDAAS. In common with process-based models, MODDAAS includes parameters whose exact value is unknown. In uncertainty analysis we consult literature and expert elicitation to provide a range of possible values (or uncertainty) on each important unknown model parameter. We then make a Monte Carlo (Latin Hypercube) sampling of this parameter uncertainty and run the model for the sample to forward the parameter uncertainty to the model predictions. This UA based uncertainty was calculated and added to the predictions from web-based decision tool. In addition, an emulator and a methodology for its creation has been developed, so that when farm observations of ammonia mitigation by tree shelter-belts become available, the uncertainty calculated in the UA can be reduced through Bayesian model calibration.

In summary our two key outcomes are:
1) Replacing the overly simple empirical model predictions in the decision tool with predictions from a model with a track-record in predicting ammonia mitigation due to trees.
2) Adding uncertainty to the predictions from the decision-tool, giving farmers crucial information on the reliability of prediction from the tool.
Exploitation Route The outcomes of this work has already been shared and is being used by the stakeholder community. As part of the DEFRA funded ART project, in-depth interviews have taken place with 5 farmers in Cumbria. The aim of this was to capture farmer's views on the practicalities and farm business benefits of tree planting to capture ammonia from hen or dairy units, to help stakeholders understand the opportunities and barriers of the practise from the farmer's perspective. As part of the interview exercise, farmers were asked to trial the new web-based decision tool, developed in MUDMAT and provide feedback on its suitability, ease of use and also to comment on the guidance information provided. We will be hearing the results from these interviews in the near future which will help guide the future further development of the web-tool. This task is part of a larger project to test how effective tree shelter belts and woodlands are at capturing ammonia emissions on poultry and dairy farms in Cumbria and to improve information for farmers on how to design a tree shelter belt.

In addition, future meetings in collaboration with key stakeholders are planned where we will present what has been created in MUDMAT. As part of this, we will pursue new funding opportunities to develop and improve the web-based decision tool further so that it can best meet the needs of the stakeholder community.
Sectors Agriculture, Food and Drink,Environment

Description DEFRA ELMS project ART - Ammonia Reduction by Trees (ECM_58624)
Amount £100,000 (GBP)
Funding ID ECM_58624 
Organisation Department For Environment, Food And Rural Affairs (DEFRA) 
Sector Public
Country United Kingdom
Start 04/2020 
End 03/2021
Title Ammonia reduction calculator ORACLE database 
Description This database contains percent recapture predictions from the coupled model OpenFOAM/MODDAAS. The columns of the database are linked to options that can be chosen in a web-based decision tool (see below). It is an ORACLE database hosted at UKCEH Edinburgh. This database provides the backend to the predictions from OpenFOAM/MODDAAS that can be accessed interactively in the new version of the web-based decision tool created in MUDMAT. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
Impact Impacts will be assessed in future years. 
Title Novel coupling of OpenFOAM to MODDAAS for ammonia mitigation by shelter-belt tree canopies predictions. 
Description This is a new coupling of the pre-existing models OpenFOAM and and MODDAAS to enable predictions of ammonia mitigation by shelter-belt tree canopies. 
Type Of Material Computer model/algorithm 
Year Produced 2020 
Provided To Others? No  
Impact The main impact of this new coupling is to provide the predictions available in the new version of the web-based decision tool created in MUDMAT.