Abstract. The Fine Resolution Atmospheric Multi-pollutantExchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO 2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data.High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.

The NERC and CEH trade marks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. Wet deposition of nitrogen and sulphur was found to decrease more slowly than the emissions reductions rate.This is attributed to a number of factors including increases in emissions from international shipping and changing rates of atmospheric oxidation. The modelled time series was extended to a 50 year period from 1970 to 2020. The modelled deposition of SO x , NO y and NH x to the UK was found to fall by 87%, 52% and 25% during this period. The percentage of the United Kingdom surface area for which critical loads are exceeded is estimated to fall from 85% in 1970 to 37% in 2020 for acidic deposition and from 73% to 49% for nutrient nitrogen deposition. The significant reduction in land emissions of SO 2 and NO X focuses further attention in controlling emissions from international shipping. Future policies to control emissions of ammonia from agriculture will be required to effect further significant reductions in nitrogen deposition.

Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned.

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This paper addresses the issue of usefulness of selected spatialization techniques for the characterization of an urban heat island (UHI). Five interpolation methods (including both deterministic and stochastic methods or their combination) -namely: inverse distance weighting (IDW), regularized spline with tension (RST), ordinary kriging (OK), multiple linear regression (MLR) and residual kriging (RK) -were evaluated for their ability to estimate air temperature in Wroc8aw, Poland, during 7 cases of the UHI. Spatial interpolation was performed based on time-adjusted air temperature data gathered by mobile measurements. Additional explanatory variables for multidimensional spatialization methods (MLR and RK) were developed based mainly on the land-use map and Landsat thematic mapper (TM) images. Statistically significant predictors were selected using a stepwise regression procedure. Parameters for optimal interpolation were chosen by cross-validation (CV) of results. The CV technique was also used to compare results obtained with the different algorithms together with evaluation of errors (e.g. root mean square error, RMSE; mean absolute error, MAE) and visual examination of the final maps. The least plausible maps, both in terms of error statistics and visually, were obtained with the IDW method. Inside the convex hull of sample points, the OK and RST techniques were characterized by simplified but acceptable air temperature surfaces. The MLR method expressed the land-use background of the UHI, even outside the convex hull, but distorted results when the process tended towards non-stationarity, e.g. due to wind influence. The most accurate results of the UHI spatialization were obtained with the RK technique. KEY WORDS: Spatialization · Spatial interpolation · Urban heat island · GIS · Wroc8awResale or republication not permitted without written consent of the publisher Clim Res 38: 171-187, 2009 This means that the isothermal pattern of an UHI is generally concentric but also strongly dependent on the spatial arrangement of the land-use types that produce local variation. The UHI shape can therefore differ from city to city and may be described as 'amoebic' (e.g. Seoul, South Korea; Park 1986) or 'multicellular ' (e.g. 1ódź, Poland;K8ysik & Fortuniak 1999).Although knowledge on the origin and consequences of UHIs has gradually increased in recent years, the accurate estimation of the UHI spatial structure, which is often needed by town planners, is still one of the most important problems. In addition, air temperature determines numerous aspects of the urban environment and data on its spatial structure is an essential input for various modelling studies (e.g. dispersion of air pollutants). However, sampling sites in the monitoring system are often sparse, limiting the application of interpolation techniques. Data gathered at meteorological stations can be supported by mobile measurements to solve data inadequacy, although some data-time adjustments are needed (Duckworth & Sandberg 1954, Kuttler ...