Spatial variance in multimedia mass balance models: comparison of LOTOS-EUROS and SimpleBox for PCB-153.

The aim of this study was to determine whether nested generic box models can be used to predict spatial variance. An inter-comparison study was performed for the nested box model SimpleBox, and the spatially resolved model LOTOS-EUROS, using PCB-153 emissions in Europe as an example. We compared the two models concerning (1) average environmental concentrations, (2) spatial concentration variances, (3) spatial concentration patterns (maps), and (4) agreement with measured concentrations for the air and soil compartments. In SimpleBox, the spatial concentration variances and patterns were calculated subsequently for each separate grid cell surrounded by a regional and a continental shell with homogeneous, averaged circumstances. Average European PCB-153 concentrations calculated by LOTOS-EUROS and SimpleBox for the period 1981-2000 agree well for the air and soil compartments. Moreover, the predicted concentrations of both models are in line with the measured PCB-153 concentrations in Europe during that period. For PCB-153, the prediction of spatial concentration variances with the nested multimedia fate model SimpleBox performs adequately in most cases, except for the lower concentration boundary in the air compartment. It is concluded that SimpleBox can be used to predict the spatial maximum and average concentrations of PCB-153 in the air and soil compartments. The proposed method has to be tested systematically for different types of compounds, emission scenarios, environmental compartments and spatial scales in order to allow conclusions about the general applicability of the method.

[1]  Kevin C Jones,et al.  Modelling the fate of persistent organic pollutants in Europe: parameterisation of a gridded distribution model. , 2004, Environmental pollution.

[2]  Y. Lei,et al.  A Comprehensive and Critical Compilation, Evaluation, and Selection of Physical–Chemical Property Data for Selected Polychlorinated Biphenyls , 2003 .

[3]  Kevin C Jones,et al.  A dynamic level IV multimedia environmental model: Application to the fate of polychlorinated biphenyls in the United Kingdom over a 60‐year period , 2002, Environmental toxicology and chemistry.

[4]  W. Shiu,et al.  Monoaromatic hydrocarbons, chlorobenzenes and PCBs , 1992 .

[5]  Thomas E McKone,et al.  Assessing the influence of climate variability on atmospheric concentrations of polychlorinated biphenyls using a global-scale mass balance model (BETR-global). , 2005, Environmental science & technology.

[6]  J. Pacyna,et al.  Towards a global historical emission inventory for selected PCB congeners--a mass balance approach. 2. Emissions. , 2002, The Science of the total environment.

[7]  O. Jolliet,et al.  Multimedia fate and human intake modeling: spatial versus nonspatial insights for chemical emissions in Western Europe. , 2005, Environmental science & technology.

[8]  J Devillers,et al.  European Union System for the Evaluation of Substances (EUSES). Principles and structure. , 1997, Chemosphere.

[9]  M. van Loon,et al.  Numerical smog prediction. I: The physical and chemical model , 1994 .

[10]  Brendan E. Hickie,et al.  Environmental Modelling: Progress and Prospects , 1997 .

[11]  Olivier Klepper,et al.  A comparison of spatially explicit and box models for the fate of chemicals in water, air and soil in Europe , 1999 .

[12]  G Heinemeyer,et al.  European union system for the evaluation of substances: the second version. , 2005, Chemosphere.

[13]  M. van Loon,et al.  Numerical smog prediction II : Grid refinement and its application to the Dutch Smog Prediction Model , 1995 .

[14]  J. Christensen,et al.  A process-oriented inter-comparison of a box model and an atmospheric chemistry transport model: Insights into model structure using α-HCH as the modelled substance , 2006 .

[15]  T. E. McKone,et al.  CalTOX, a multimedia total exposure model for hazardous-waste sites; Part 1, Executive summary , 1993 .

[16]  D Mackay,et al.  The evolution of mass balance models of persistent organic pollutant fate in the environment. , 1999, Environmental pollution.

[17]  W. Shiu,et al.  Illustrated handbook of physical-chemical properties and environmental fate for organic chemicals. Volume 5: pesticide chemicals. , 1992 .

[18]  Yuichi Moriguchi,et al.  Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches. , 2004, Environmental science & technology.

[19]  Frank Dentener,et al.  Secondary inorganic aerosol simulations for Europe with special attention to nitrate , 2004 .

[20]  C. E. Cowan,et al.  The Multi-Media Fate Model: A Vital Tool for Predicting the Fate of Chemicals, , 1995 .

[21]  James L. Kinter,et al.  The Grid Analysis and Display System (GRADS) , 1991 .

[22]  Renske Timmermans,et al.  The LOTOS?EUROS model: description, validation and latest developments , 2008 .

[23]  F. D. Leeuw,et al.  Modeling study of SOx and NOx transport during the January 1985 SMOG episode , 1990 .

[24]  D W Pennington,et al.  Evaluating multimedia/multipathway model intake fraction estimates using POP emission and monitoring data. , 2004, Environmental pollution.

[25]  F. Wania Spatial variability in compartmental fate modelling , 1996, Environmental science and pollution research international.

[26]  Thomas M Cahill,et al.  A high-resolution model for estimating the environmental fate of multi-species chemicals: application to malathion and pentachlorophenol. , 2003, Chemosphere.