Diagnostic indicators of elevated nitrogen deposition

Pitcairn, C. E. R.; Fowler, D.; Leith, Ian D.; Sheppard, Lucy J.; Tang, Sim; Sutton, Mark A.; Famulari, D.

doi:10.1016/j.envpol.2006.01.049

Cited by 101 publications

(74 citation statements)

References 27 publications

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“…The results vary widely, showing recapture fractions within the first 2 km between 2 % and up to 60 %, but in most cases in the range between 10 % and 40 % (Loubet et al, 2006. The variability is in part due to variations in vegetation types, roughness and LAI over the patchwork of land uses, but also due to the nitrogen enrichment associated with large NH 3 deposition rates close to sources (animal houses, manure storage facilities, fertilized fields) (Pitcairn et al, 2006). Given an otherwise homogeneous, large field (a few hectares) cropped with, say, wheat or maize, and located just outside a large point animal production facility, one may expect a 10-or 20-fold higher NH 3 deposition at a distance of 20 m from the source than 200 m further downwind .…”

Section: Landscape Scale Modelsmentioning

confidence: 98%

“…The intercomparison focused on atmospheric NH 3 concentration prediction in two case study farms in Denmark and the USA. Wet deposition processes were not included in the simulations because dry deposition is likely the dominant deposition mechanism near sources Pitcairn et al, 2006). Similarly, chemical processing of NH 3 in the atmosphere were also assumed to be negligible for short-range dispersion.…”

Section: Landscape Scale Modelsmentioning

confidence: 99%

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Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

et al. 2013

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Atmospheric ammonia (NH₃) dominates global emissions of total reactive nitrogen (N_r), while emissions from agricultural production systems contribute about two-thirds of global NH₃ emissions; the remaining third emanates from oceans, natural vegetation, humans, wild animals and biomass burning. On land, NH₃ emitted from the various sources eventually returns to the biosphere by dry deposition to sink areas, predominantly semi-natural vegetation, and by wet and dry deposition as ammonium (NH₄⁺) to all surfaces. However, the land/atmosphere exchange of gaseous NH₃ is in fact bi-directional over unfertilized as well as fertilized ecosystems, with periods and areas of emission and deposition alternating in time (diurnal, seasonal) and space (patchwork landscapes). The exchange is controlled by a range of environmental factors, including meteorology, surface layer turbulence, thermodynamics, air and surface heterogeneous-phase chemistry, canopy geometry, plant development stage, leaf age, organic matter decomposition, soil microbial turnover, and, in agricultural systems, by fertilizer application rate, fertilizer type, soil type, crop type, and agricultural management practices. We review the range of processes controlling NH₃ emission and uptake in the different parts of the soil-canopy-atmosphere continuum, with NH₃ emission potentials defined at the substrate and leaf levels by different [NH₄⁺] / [H⁺] ratios (Γ). Surface/atmosphere exchange models for NH₃ are necessary to compute the temporal and spatial patterns of emissions and deposition at the soil, plant, field, landscape, regional and global scales, in order to assess the multiple environmental impacts of airborne and deposited NH₃ and NH₄⁺. Models of soil/vegetation/atmosphere NH₃ exchange are reviewed from the substrate and leaf scales to the global scale. They range from simple steady-state, "big leaf" canopy resistance models, to dynamic, multi-layer, multi-process, multi-chemical species schemes. Their level of complexity depends on their purpose, the spatial scale at which they are applied, the current level of parameterization, and the availability of the input data they require. State-of-the-art solutions for determining the emission/sink Γ potentials through the soil/canopy system include coupled, interactive chemical transport models (CTM) and soil/ecosystem modelling at the regional scale. However, it remains a matter for debate to what extent realistic options for future regional and global models should be based on process-based mechanistic versus empirical and regression-type models. Further discussion is needed on the extent and timescale by which new approaches can be used, such as integration with ecosystem models and satellite observations

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Section: Landscape Scale Modelsmentioning

confidence: 98%

Section: Landscape Scale Modelsmentioning

confidence: 99%

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

et al. 2013

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“…As biomonitors of atmospheric N depositions, mosses can potentially be used for identifying areas at risk from high N deposition (Harmens et al, submitted) (Pitcairn et al, 2006). The conversion of the N concentrations in mosses to spatially highly resolved N deposition maps could be done by applying regression kriging as described by Hengl et al (2007).…”

Section: Discussionmentioning

confidence: 99%

“…These other geodata include four site-specific characteristics and 19 regional characteristics which might influence the N concentration in mosses (Böhlmann et al, 2005;Bytnerowicz et al, 2002;Bytnerowicz and Fenn, 1996;Fenn et al, 2007;Fenn and Kiefer, 1999;Fernandez and Carballeira, 2002;Fowler et al 1998;Frati et al, 2007;Jovan and Carlberg, 2007;Jovan and Mccune, 2006;Luo et al, 2003;Neirynck et al, 2007;Pesch et al, 2007b;Pitcairn et al, 2006). Together with the EMEP data the site-specific and regional characteristics are referred to as predictors in the CART-analysis (see Section 2.4).…”

Section: Additional Geodatamentioning

confidence: 99%

“…Carpet-forming ectohydric mosses might potentially be used as biomonitors of atmospheric N deposition as well (Pitcairn et al, 1995(Pitcairn et al, , 2006Poikolainen et al 2009;Salemaa et al, 2008;Solga et al, 2005;Zechmeister et al 2008). A pilot-study in Scandinavian countries showed a strong linear relationship between the total N concentration in mosses and EMEP-modelled atmospheric N deposition rates (Harmens et al, 2005).…”

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First Europe-wide correlation analysis identifying factors best explaining the total nitrogen concentration in mosses

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Atmospheric Environment

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Review and Integration of Biosphere-Atmosphere Modelling of Reactive Trace Gases and Volatile Aerosols

2015

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Diagnostic indicators of elevated nitrogen deposition

Cited by 101 publications

References 27 publications

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

Advances in understanding, models and parameterizations of biosphere-atmosphere ammonia exchange

First Europe-wide correlation analysis identifying factors best explaining the total nitrogen concentration in mosses

Review and Integration of Biosphere-Atmosphere Modelling of Reactive Trace Gases and Volatile Aerosols

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