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

Lead Research Organisation: NERC Centre for Ecology and Hydrology
Department Name: Atmospheric Chemistry and Effects

Abstract

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.

Publications

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 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
 
Description French National Institute for Agriculture, Food, and Environment (INRAE) 
Organisation French National Institute of Agricultural Research
Country France 
Sector Academic/University 
PI Contribution We are helping INRA quantify the parametric uncertainty in their model OpenFOAM-MODDAS using Bayesian statistical analysis techniques.
Collaborator Contribution They are providing us with modelling expertise and understand as well as the model INRA model MODDAS (pollutant deposition model). They also will help us assess the adequacy of the statistical emulator that we are creating in MUDMAT.
Impact Thus far this interdisciplinary corroboration has enabled us to port the model OpenFOAM-MODDAS to the JASMIN cluster machine. Further outputs will come as the project proceeds.
Start Year 2019