Dry deposition of reactive nitrogen to European ecosystems: a comparison of inferential models across the NitroEurope network

C. R. Flechard, E. Nemitz, R. I. Smith, D. Fowler, A. T. Vermeulen, A. Bleeker, J. W. Erisman, D. Simpson, L. Zhang, Y. S. Tang, M. A. Sutton
2010 Atmospheric Chemistry and Physics Discussions  
Inferential models have long been used to determine pollutant dry deposition to ecosystems from measurements of air concentrations and as part of national and regional atmospheric chemistry and transport models, and yet models still suffer very large uncertainties. An inferential network of 55 sites throughout Europe for atmospheric reactive nitrogen (N r ) was established in 2007, providing ambient concentrations of gaseous NH 3 , NO 2 , HNO 3 and HONO and aerosol NH + 4 and NO − 3 as part of
more » ... NO − 3 as part of the NitroEurope Integrated Project. Network results providing modelled inorganic N r dry deposition to the 55 monitoring sites are presented, using four existing dry deposition routines, revealing inter-model differences and providing ensemble average deposition estimates. Dry deposition is generally largest over forests in regions with large ambient NH 3 concentrations, exceeding 30-40 kg N ha −1 yr −1 over parts of the Netherlands and Belgium, while some remote forests in Scandinavia receive less than 2 kg N ha −1 yr −1 . Turbulent N r deposition to short vegetation ecosystems is generally smaller than to forests due to reduced turbulent exchange, but also because NH 3 inputs to fertilised, agricultural systems are limited by the presence of a substantial NH 3 source in the vegetation, leading to periods of emission as well as deposition. Differences between models reach a factor 2-3 and are often greater than differences between monitoring sites. For soluble N r gases such as NH 3 and HNO 3 , the non-stomatal pathways are responsible for most of the annual uptake over many surfaces, especially the non-agricultural land uses,
doi:10.5194/acpd-10-29291-2010 fatcat:ouakpnovt5d5tkxlt5ozbqhpeq