Abstract.Nitrate is an important component of (secondary inorganic) fine aerosols in Europe. We present a model simulation for the year 1995 in which we account for the formation of secondary inorganic aerosols including ammonium sulphate and ammonium nitrate, a semi volatile component. For this purpose, the chemistry-transport model LOTOS was extended with a thermodynamic equilibrium module and additional relevant processes to account for secondary aerosol formation and deposition. During winter, fall and especially spring high nitrate levels are projected over north western, central and eastern Europe. During winter nitrate concentrations are highest in Italy, in accordance with observed data. In winter nitric acid, the precursor for aerosol nitrate is formed through heterogeneous reactions on the surface of aerosols. Modelled and observed sulphate concentrations show little seasonal variation. Compared to sulphate levels, appreciable ammonium nitrate concentrations in summer are limited to those areas with high ammonia emissions, e.g. the Netherlands, since high ammonia concentrations are necessary to stabilise this aerosol component at high temperatures. As a consequence of the strong seasonal variation in nitrate levels the AOD depth of nitrate over Europe is especially significant compared to that of sulphate in winter and spring when equal AOD values are calculated over large parts of Europe. Averaged over all stations the model reproduces the measured concentrations for NO 3 , SO 4 , NH 4 , TNO 3 (HNO 3 +NO 3 ), TNH 4 (NH 3 +NH 4 ) and SO 2 within 20%. The daily variation is captured well, albeit that the model does not always represent the amplitude of single events. The model underestimates wet deposition which was attributed to the crude representation of cloud processes.Comparison of retrieved and computed aerosol optical depth (AOD) showed that the model underestimates AOD signifiCorrespondence to: M. Schaap (m.schaap@mep.tno.nl) cantly, which was expected due to the lack of carbonaceous aerosols, sea salt and dust in the model. The treatment of ammonia was found to be a major source for uncertainties in the model representation of secondary aerosols. Also, inclusion of sea salt is necessary to properly assess the nitrate and nitric acid levels in marine areas.

This paper examines a class of explicit finite-difference advection schemes derived along the method of lines. An important application field is large-scale atmospheric transport. The paper therefore focuses on the demand of positivity. For the spatial discretization, attention is confined to conservative schemes using five points per direction. The fourth-order central scheme and the family of K-schemes, comprising the second-order central, the second-order upwind, and the third-order upwind biased, are studied. Positivity is enforced through flux limiting. It is concluded that the limited third-order upwind discretization is the best candidate from the four examined. For the time integration attention is confined to a number of explicit Runge-Kutta methods of orders two up to four. With regard to the demand of positivity, these integration methods turn out to behave almost equally and no best method could be identified. '~' 1995 Academic Press, Inc. l. INTRODUCTIONThe subject of this paper is the numerical solution of the partial differential equation for linear advection of a scalar quantity w in an arbitrary velocity field u, given byLinear advection is an important (classical) problem in computational fluid dynamics and has been the subject of numerous investigations. The central theme is how to approximate the advection term \7 · (uw), such that the resulting errors in both phase and amplitude are minimized and the computational cost is still affordable. An important application we have in mind concerns atmospheric transport of chemical species. Then w represents a concentration or density and u a wind field. In addition to the usual accuracy and efficiency requirements, here the main consideration is that the transported concentrations must remain positive, because in actual applications also chemical reactions are modeled for which positivity is a prerequisite for avoiding non-physical chemical instabilities. We emphasize *The research reported helongs to the projects EUSMOG and CIRK which are carried out in cooperation with the Air Laboratory of the RIVM-Tbe Dutch National Institute of Public Health and Environmental Protection. The RIVM is acknowledged for financial support. 35that the demand of positivity is important and that it severely restricts the choice of method, as it is essentially equivalent to the demand of avoiding numerical under-and overshoots in regions of strong variation.The research objective of this paper is to ex.amine a class of positive, finite-difference advection schemes which we consider promising for atmospheric transport applications and to select from this class the best possible candidate. We hereby follow the method-of-lines approach which means that the spatial discretization and temporal integration are considered separately.For the spatial discretization we confine ourselves to stencils using five points per (spatial) direction. We consider this a good starting point since a 5-point stencil is computationally attractive for the following reasons. First, a 5-point stenc...

Abstract-In many applications of atmospheric transport-chemistry problems, a major task is the nwnerical integration of the stiff systems of ordinary differential equations describing the chemical transformations. This paper presents a comprehensive numerical comparison between five dedicated explicit and four implicit solvers for a set of seven benchmark problems from actual applications. The implicit solvers use sparse matrix techniques to economize on the numerical linear algebra overhead. As a result they are often more efficient than the dedicated explicit ones, particularly when approximately two or more figures of accuracy are required. In most test cases, sparse RODAS, a Rosenbrock solver, came out as most competitive in the 1 % error region. Of the dedicated explicit solvers, TWOSTEP came out as best. When less than 1 % accuracy is aimed at, this solver performs very efficiently for tropospheric gas-phase problems. However, like all other dedicated explicit solvers, it cannot efficiently deal with gas-liquid phase chemistry. The results presented may constitute a guide for atmospheric modelcrs to select a suitable integrator based on the type and dimension of their chemical mechanism and on the desired level of accuracy. Furthermore, we would like to consider this paper an open invitation for other groups to add new representative test problems to those described here and to benchmark their numerical algorithms in our standard computational environment.© 1997 Elsevier Science Ltd.

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[1] We present a model simulation for the year 1995 accounting for primary particles, which are an important component of fine aerosols over Europe. A new emission inventory for black carbon (BC) was developed on the basis of the recent European emission inventory of anthropogenic primary particulate matter (Coordinated European Programme on Particulate Matter Emission Inventories, Projections and Guidance (CEPMEIP)). The annual BC emissions of Europe and the former Soviet Union for 1995 are estimated at 0.47 and 0.26 Tg C, respectively, with highest contributions from transport (off-road and onroad) and households. Modeled BC concentrations range from 0.05 mg/m 3 in remote regions to more than 1 mg/m 3 over densely populated areas. The modeled BC concentration is about 25% of the total primary aerosol concentration. The primary aerosol fields were combined with previously calculated secondary aerosol concentrations to obtain an estimate of the total anthropogenic fine aerosol distribution. Modeled BC levels contribute only 4-10% to fine aerosol mass, whereas sulphate and nitrate contribute 25-50 and 5-35%, respectively. Comparison with experimental data revealed that the model underestimates PM2.5 levels, mostly caused by the underprediction of total carbonaceous material (BC and OC) by a factor of $2. The underestimation can partly be explained by the influence of local emissions, measurement uncertainties, natural sources, and representation of wet deposition. However, the uncertainties associated with the emission inventory for BC (and total PM) may be the most important cause for the discrepancy. In comparison with previous studies, our BC emission estimate is a factor of 2 lower, caused by the choice of more recent emission factors. Therefore a better knowledge of emission factors is urgently needed to estimate the BC (and PM) emissions reliably.