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Uncertainty in mass balance critical loads and exceedance: Application to a UK national data set

Heywood, Liz; Hall, Jane; Smith, Rognvald. 2006 Uncertainty in mass balance critical loads and exceedance: Application to a UK national data set. Atmospheric Environment, 40. 6146-6153. 10.1016/j.atmosenv.2006.05.030

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Abstract/Summary

It is generally accepted that uncertainty should be taken into account in environmental assessments and the subsequent decision-making. This paper undertakes an uncertainty assessment for acidity and nutrient nitrogen critical loads and their exceedances, which is important in determining national and international policy on the emissions of acidifying air pollutants. This is the first time such an analysis has been done for the UK at the national scale. In this paper we illustrate the process and issues with reference to “managed coniferous woodland”, one of a number of habitat types for which critical loads are calculated. Again using coniferous woodland as an example Monte Carlo analysis showed that the uncertainties in the national critical loads varied between 14 and 29%. Policy makers are however primarily concerned with whether the critical load is exceeded and therefore the uncertainty in exceedance is also estimated. Again using coniferous woodland as an example, Monte Carlo analysis showed that for acidity, it was uncertain whether the critical load was exceeded or not for the majority of the coniferous woodland habitat. For nutrient nitrogen, most of the habitat had a very high probability of exceedance.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1016/j.atmosenv.2006.05.030
Programmes: CEH Programmes pre-2009 publications > Biogeochemistry
UKCEH and CEH Sections/Science Areas: _ Atmospheric Sciences
_ Ecological Risk
ISSN: 1352-2310
Additional Keywords: acidification, eutrophication, policy, Monte Carlo
NORA Subject Terms: Data and Information
Atmospheric Sciences
Date made live: 07 May 2008 08:48 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/2868

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