Modelling urban ozone in RAINS

For modelling urban ozone into RAINS for the purposes of health impact assessment, a similar approach as for PM is envisaged. Thereby, the regional-scale source-receptor relationships will be derived from the EMEP model, which will then deliver for an emission scenario the rural background concentrations of ozone for the grid cell where a city is located. A further step will then modify these rural concentrations to reflect the population-related characteristic ozone exposure. Initial analysis from the City-Delta emission and monitoring data reveals a striking relationship of the difference between rural and urban ozone levels and NOx emission densities. Further work will be conducted to further explore this aspect, to include the location of population within the city and to implement it within the RAINS analysis.

y = 0.2122x - 0.8072 R² = 0.9198

-1.00 -0.50 0.00 0.50 1.00 1.50 2.00 2.50

0.00 5.00 10.00 15.00

Series1

Linear (Series1)

Figure 6.12: Decrease in urban long-term (summer mean) ozone compared to rural background level (in ppb) as a function of changes in NOx emission densities in the urban model domain (t/km²) for five City-Delta cities (Berlin, London, Milan, Paris, Prague). This graph is derived from the City-Delta ensemble solutions for the CLE and NOx-MFR scenarios.

6.3 Uncertainties

As explained above, many aspects load any estimate of health impacts of ozone with significant uncertainties. For quantification of the health-relevant air quality changes resulting from emission

changes, the general imperfections of dispersion modelling for ozone cannot be eliminated in the near future.

Thus, it is even more important to design the integrated assessment model system in such a way as to minimize the potential influence of the unavoidable uncertainties and maximize the robustness of model results. A key element in this task will be the choice of the appropriate ozone metric that will be used for the health impact assessment.

While the specific approach for uncertainty treatment within the integrated assessment model can only be designed once the model approach has been ultimately decided (i.e., after all results from the EMEP dispersion model and City-Delta are finally available), preparatory actions have been taken to derive quantified estimates of the uncertainties of the various elements in the model chain. City-Delta by its design provides inter alia information about the extent of agreement and disagreement among the available state-of-the-art urban dispersion models.

6.3.1 The Euro-Delta project

To gain insight into the performance of regional scale models and obtain an overall feeling of present uncertainties of the state-of-the-art dispersion models for ozone, IIASA together with the Institute for Environment and Sustainability of the Joint Research Centre (Ispra), MET.NO, EUROTRAC-2 and CONCAWE, has initiated the Euro-Delta model intercomparison (http://rea.ei.jrc.it/netshare/thunis/eurodelta/). The aim of this exercise is to conduct a systematic comparison of regional scale dispersion models to judge the performance of state-of-the-art regional scale dispersion models in relation to health- and policy-relevant model output.

Five European scale dispersion models including the EMEP Eulerian model participate in this intercomparison (Table 5.5), which analyses model responses for PM and ozone for seven emission control scenarios. More detail on the set-up is given in the health PM Chapter.

Table 6.1: Participating models in Euro-Delta

Model Contact person Affiliation

LOTOS P. Builtjes TNO-MEP, (NL)

REM3/CALGRID R. Stern FUB, (D)

CHIMERE C. Honore L. Rouil INERIS, (F)

Unified EMEP L. Tarrason EMEP/MSC-W, (N)

MATCH J. Langner SMHI (S)

MODELS-3 I. Rodgers INNOGY, (GB)

Figure 6.13 compares the summer mean ozone concentrations calculated with the Euro-Delta models with observations for German EMEP monitoring sites.

Figure 6.13: Summer mean ozone concentrations computed by the Euro-Delta models for the German monitoring stations (in ppb). The black bar indicates observations

Comparisons have been started to explore differences in model responses towards changes in emissions. As an example, Figure 6.14 presents for a number of European regions changes in summer mean ozone concentrations (calculated from daily model results) for a number of emission control scenarios. The x-axis lists the various regions in Europe (00=Europe, 01=Austria, 08=France, 09=Germany, 12=Italy, 14=Netherlands, 19=Spain, 22=British Isles. The lines indicate the range of model results (green=highest result of all participating models, blue=lowest result, red=ensemble model, calculated from all models as the median of the daily results). The first two panels provide summer mean ozone for the emissions of 2000 and CLE2010. The others indicate the percentage changes in relation to the values of 2000 or CLE for the various emission control cases (CLE, NOx -MFR, VOC--MFR, NOx+VOC-MFR, as well as for the ensemble model the difference between the joint NOx/VOC case and the sums of the individual NOx and VOC changes (i.e., the error from a linearity assumption). In most cases, the response of the EMEP model is close to the ensemble model.

Figure 6.14: Responses of European scale dispersion models to changes in precursor emissions for different regions in Europe. Details are given in the text.

6.4 State of progress and plans for further work

At the moment, IIASA has received the first 87 model experiments from the new EMEP Eulerian model and started an in-depth analysis of the model behaviour. Next steps include:

determining the linearity of regional scale dispersion of ozone within the given emission constraints, constructing appropriate regional-scale source-receptor relationships,

developing and implementing the urban module of RAINS,

bringing the Euro-Delta exercise to a conclusions and draw the lessons for the uncertainty analysis, designing and implementing the health impact assessment for ozone as suggested by the UN/ECE-WHO Task Force on Health with the final model set-up, and

• assess the overall uncertainties of the health impact assessment.

6.5 References

Amann, M. and Lutz, M. (2000) The revision of the air quality legislation in the European Union related to ground-level ozone. Journal of Hazardous Materials 78: 41-62.

Heyes, C., Schöpp, W., Amann, M. and Unger, S. (1996) A Reduced-Form Model to Predict Long-Term Ozone Concentrations in Europe. WP-96-12, International Institute for Applied Systems Analysis, Laxenburg, Austria.

Rabl, A. (2003) Interpretation of Air Pollution Mortality:Number of Deaths or Years of Life Lost?

Journal of the Air & Waste Management Association 53(1): 41-50.

TFH (2003) Modelling and assessment of the health impact of particulate matter and ozone.

EB.AIR/WG.1/2003/11, United Nations Economic Commission for Europe, Task Force on Health, Geneve.

TFMM (2003) Review of the Unified EMEP model. Summary report and conclusions of the workshop of the EMEP Task Force on Monitoring and Modelling. United Nations Economic

Commission for Europe, Geneva.

7 Modelling of vegetation impacts of ground-level ozone