An experience on modelling-based assessment of the air quality within the Air Quality Directive framework Ana Isabel Miranda, Isabel Ribeiro, Patrícia Fernandes, Alexandra Monteiro, Cristina Monteiro, Carlos Borrego

Concentration Fixed measurements shall be used Combination of fixed measurements and modelling techniques and or indicative measurements may be used Upper assessment threshold Lower assessment threshold Modelling techniques or objective- estimation shall be sufficient SO 2, NO 2, NOx, PM10, PM2,5, Pb, C 6 H 6, CO Those fixed measurements may be supplemented by modelling techniques and/or indicative measurements to provide adequate information on the spatial distribution of the ambient air quality Air Quality Directive| air quality assessment Assessment strategy depends on upper and lower assessment thresholds

Exceedances of upper and lower assessment thresholds shall be determined on the basis of concentration during the previous 5 years where sufficient data are available. An assessment threshold shall be deemed to have been exceeded if it has beed exceed during at least 3 separate years out of those previous five years. Assessment for 2010 and 2011 Upper and lower thresholds exceedances for (5 years period).

Modelling 1. Model application to Portugal (5 km x 5 km), 2010 and Bias correction based on the multiplicative ratio adjustment technique 3. Evaluation (using the DELTA tool when possible) The approach Monitoring 1. Monitoring stations selection and data treatment, for the period Comparison with the upper and lower thresholds, for every pollutant data treatment for the model evaluation AQ assessment based on a combination of Modelling and Measuring values NO 2, O 3, PM10, PM2.5, SO 2, CO, C 6 H 6.

MM5-EURAD Meteorological conditions Emissions

125x125 km 2 25x25 km 2 5x5 km 2 Simulation domains

Emissions EMEP 2008 for the larger domains Portuguese inventory 2008 for the portuguese domain Transports Industrial processes

Monitoring stations

SUBST an additive correction of the mean bias RAT a multiplicative ratio correction We started to compare… Bias-correction techniques

after BIAS correction, model results have a decrease > 70% on the average systematic error the multiplicative ratio: better correction technique Bias-correction techniques RAT & SUBST synoptic conditions are characterized by a 3-4 day period. (Borrego et al., 2011, Atmospheric Environment) O3O3 PM10

PM10 daily average (2010) Ervedeira monitoring station

NO 2 maximum daily (2010) Ervedeira monitoring station obs RAT04 original

Validation SO 2 Hourly values – Calendário 2010 RDE = 15%; R = 0.63;bias = µg.m -3 ; MSE = 4.31 µg.m -3 measured modelled

SO 2 4 th maximum of the daily averages (protection of human health) Threshold values were not exceeded Upper Lower LV Zones and agglomerations

SO It was not possible to have the needed data everywhere 4 th maximum of the daily averages (protection of human health) < LAT LAT-UAT > UAT

SO 2 Annual average winter period (ecosystem protection) < LAT LAT-UAT >UAT

SO 2 Modelling results CORINE Land Cover 2006 GIS Annual average winter period (ecosystems protection)

SO 2 25 th maximum hourly value LV

Validation NO 2 Hourly data

Validation NO 2 Hourly data

NO 2 Annual mean Zones and agglomerations Upper Lower LV

NO 2 Annual mean LV < LAT LAT-UAT > UAT

NO 2 Annual mean Modelling results Population data at sub- municipality level GIS National roads network

NO 2 19 th maximum of the hourly averages (protection of human health) Zones and agglomerations Upper Lower LV

NO th maximum of the hourly averages < LAT LAT-UAT > UAT LV

NO 2 19 th maximum of the hourly averages

NO 2 Number of hours exceeding the LV

Validation PM10 Daily average

Validation PM10 Daily average

PM10 Annual average < LAT LAT-UAT > UAT LV

PM10 Daily average < LAT LAT-UAT > UAT LV

Notwithstanding this modelling work no modelling-based report to the Comission was delivered. This work was requested by the Portuguese Agency for the Environment. It was presented to the national agency and to the different regional entities in charge of the air quality assessment in Portugal. Several comments and feedbacks were received. They were very interested and willing to do a cost-benefit analysis of using modelling tools and reducing monitoring stations instead of keeping the maintenance costs they’re facing nowadays. We’re doing 2012 and we’re going to increase spatial resolution. Final comments

But … There is a strong difficulty to trust models and people is afraid of using them, because: they were always working with AQ monitoring networks and that’s what they know they think models are a kind of “monster” and they do not provide a really added value February 2009

Attitude towards models changed and people are much more receptive to their use for air quality assessment. Thanks to FAIRMODE!!!!

Thank you very much!!!