Elsevier

Atmospheric Environment

Volume 43, Issue 5, February 2009, Pages 1029-1036
Atmospheric Environment

SIMAIR—Evaluation tool for meeting the EU directive on air pollution limits

https://doi.org/10.1016/j.atmosenv.2008.01.056Get rights and content

Abstract

Almost all Swedish cities need to determine air pollution levels—especially PM10—close to major streets. SIMAIR is an internet tool that can be used by all Swedish municipalities to assess PM10, NO2, CO and benzene levels and how they compare to the EU directive. SIMAIR is delivered to the municipalities with all required input data pre-loaded and is meant to be used prior to decisions if and where, monitoring campaigns are required. The system includes a road and vehicle database with emission factors and a model to calculate non-tailpipe PM10 emissions. Regional and urban background contributions are pre-calculated and stored as hourly values on a 1×1 km2 grid. The local contribution is calculated by the user, selecting either an open road or a street canyon environment.

A comparison between measured and simulated concentrations in four street locations shows that SIMAIR is able to calculate statistics of yearly mean values, 90-percentile and 98-percentile daily mean values and the number of days exceeding the limit value that are well within ±50% that EU requires for model estimates of yearly mean values. In comparison, all values except one are within ±25% which is the quality objective for fixed measurements according to the EU directive.

The SIMAIR model system is also able to separate the percentual contribution of the long-range transport from outside the city, the city contribution and the local contribution from the traffic of an individual street.

Introduction

The EU directive on air pollution levels for PM10, NO2, CO and benzene (EU, 2005), mirrored in Swedish legislation, has far reaching consequences for Swedish city administrations. Of special importance is the PM10 legislation, as the Swedish EPA estimates that around 80% of 350 population centers—some with less than 10,000 inhabitants—will have to assess PM10 concentrations. The critical levels are generally expected to be caused by local traffic emissions (for PM10 this includes non-exhaust emissions) together with long-range transport from sources outside Sweden. Also NO2 levels are close or above the legislation limits in a number of cities, while CO and benzene are not expected to exceed the standards in any Swedish city.

In Sweden the long-range transport is especially important for the urban background PM10 levels, typically contributing, as a yearly average, to 70% in the southern parts and 50% in the northern parts of the country (Forsberg et al., 2005). Also NO2 has a significant long-range component and the local NO/NO2 ratio has a strong dependence on the ozone concentrations in the incoming air.

An important characteristic of the PM10 levels in Scandinavian cities is the domination of non-exhaust PM emissions as compared to combustion particles. In Stockholm, the emission of mechanically generated particles, mostly due to road and tyre wear, is as a yearly average eight times higher than the emission of vehicle exhaust particles (Forsberg et al., 2005). This exceptionally high non-exhaust emission, as compared to other parts of Europe, is explained by the wintertime use of studded tyres in combination with sand/salt antiskid treatment on the roads.

The fact that the EU directive includes upper concentration limits for percentiles of daily averages prevents from the use of simple superposition of the regional, the urban and the local contributions. Episodes of high regional contributions may be correlated or anti-correlated with high local contributions (low mixing). The SIMAIR system is therefore based on hourly time series calculations of the different contributions. This allows a straightforward statistical treatment of the simulated concentrations before comparing with EU standards.

The SIMAIR system, except being an advanced coupled model system, also includes a traffic emission database covering the entire road network of Sweden. The end user of SIMAIR, found at municipality level, can directly perform model calculations close to streets in his own area, as all input data are preloaded. A highly efficient user interface, accessed from an ordinary Internet browser, allows for a GIS-like operation of the system.

Section snippets

Methods

The characteristics of the SIMAIR system are to use the best available emission and dispersion models on different scales, but at the same time present a very simplified functionality. Small city administrations do not have personal or economical resources to spend much time on following up air quality standards. All information needed should be available on delivery of the evaluation tool and the time to get an answer for a particular road link should be as close as possible to immediate. A

Validation results

According to EU directives on ambient air quality, the uncertainty for modeling estimation is defined as the maximum deviation of the measured and the calculated concentration levels, over the period considered and at the limit value in consideration, without taking into account the timing of the events. Modeling uncertainty for PM10 is defined for annual average to ±50%. For daily average it is not yet defined, but we use the same percentages also for the comparison of measured and calculated

Discussion and conclusions

The EU legislation regulates air quality to protect the health of the population. The Swedish application of the EU directive points out individual municipalities to show compliance with limit values. For population centers with more than 10,000 inhabitants there is a need for air quality monitoring, if not the municipalities can show with objective estimations that the air quality levels are well below the lower evaluation threshold. For PM10 this latter threshold is just 10 μg m−3, commonly

Acknowledgments

The development of SIMAIR has been funded by the Swedish Environmental Protection Agency and the Swedish Road Administration.

References (16)

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