Bias Correction Techniques to Improve Air Quality Ensemble Predictions: Focus on O3 and PM Over Portugal

Monteiro, A.; Ribeiro, Isabel; Tchepel, Oxana; Sá, E.; Ferreira, Joana; Carvalho, Anabela; Martins, V.; Strunk, A.; Galmarini, Stefano; Elbern, Hendrik; Schaap, Martijn; Builtjes, P.; Miranda, Ana Isabel; Borrego, Carlos

doi:10.1007/s10666-013-9358-2

Cited by 29 publications

(23 citation statements)

References 29 publications

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“…This modelling system has been already exhaustively tested and validated for the Portugal region with results confirming a very good model performance and high skills for O 3 in particular (Monteiro et al 2013a(Monteiro et al , 2013b). The WRF model, from the National Center for Atmospheric Research (NCAR) (Skamarock and Klemp 2008), version 3.5., is a next-generation mesoscale numerical weather prediction system designed to serve both operational forecasting and atmospheric research needs.…”

Section: Air Quality Modelling Applicationmentioning

confidence: 74%

“…For SNAP 7, emissions by municipality were disaggregated considering the road network of each municipality, with emissions being allocated to the cells of the domain occupied by roads, taking into account the traffic volume by road type. For SNAPs 2, 3, 4, 5, 6, 9 and 10, emissions were disaggregated by parish, based on socioeconomic factors appropriate for each sector of activity, such as fuel consumption and population density (Monteiro et al 2007(Monteiro et al , 2013b.…”

Section: Air Quality Modelling Applicationmentioning

confidence: 99%

See 1 more Smart Citation

Air quality plan for ozone: an urgent need for North Portugal

Borrego

Monteiro

Martins

et al. 2015

Air Qual Atmos Health

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Each summer period, ozone concentrations surpass the legislation limits in the north of Portugal, more precisely at the Douro Norte monitoring station. To solve/mitigate this air pollution problem, and respond to the EU requirements, air quality plans were studied and designed. An air quality numerical modelling system was applied, with a source apportionment technique (to the most relevant ozone episodes) to identify the major source regions and the main activity sectors responsible for the ozone values at this site. Modelling results pointed out that the background values contribute with more than 50 % to the ozone concentration measured, followed by transport and residential sectors-the main anthropogenic activities. More regional and transboundary strategies are needed to reduce the background concentrations, besides local actions on road transport and residential combustion at urban regions (e.g., the Porto area).

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Section: Air Quality Modelling Applicationmentioning

confidence: 74%

Section: Air Quality Modelling Applicationmentioning

confidence: 99%

Air quality plan for ozone: an urgent need for North Portugal

Borrego

Monteiro

Martins

et al. 2015

Air Qual Atmos Health

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“…It includes 3DVar and 4DVar chemical data assimilation and is able to run in nesting mode. EURAD-IM has been applied on several recent air pollution studies (Monteiro et al, 2013;Zyryanov et al, 2012;Monteiro et al, 2012;Elbern et al, 2011;Kanakidou et al, 2011).…”

Section: Eurad-im Forecast and Analysis Systemmentioning

confidence: 99%

A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

et al. 2015

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Abstract. This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multimodel ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O 3 , NO 2 , SO 2 , CO, PM 10 , PM 2.5 , NO, NH 3 , total NMVOCs (non-methane volatile organic compounds) and PAN+PAN Published by Copernicus Publications on behalf of the European Geosciences Union. V. Marécal et al.:A regional air quality forecasting system over Europe precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations.The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO 2 and PM 10 . The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 µg m −3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30-50 µg m −3 . Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM 10 for winter 2013-1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 µg m −3 . The ensemble median fractional gross error is larger for PM 10 (∼ 0.52) than for ozone and the correlation is lower (∼ 0.35 for PM 10 and ∼ 0.54 for ...

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“…The previous evaluation/validation exercises performed for this modeling system were fundamental to support and guarantee the analysis of these model results. In several previous works (Monteiro et al, 2013a;Monteiro et al, 2013b) the EURAD modeling results were compared with observations from the air quality monitoring stations, for the several air pollutants and for a long period (one year) and also inter-compared with other air quality models. The results point out a very good correspondence between simulated and observed values for the various species, with a RMSE is, in average, below 20 μg m -3 ; BIAS below -10 μg m -3 for the different pollutants (namely O3, NOX and PM10) and the correlation coefficient, in average, above 0.7 for O3 and above 0.6 for PM10 and NOX.…”

Section: Air Quality Over Portugal For the Year 2020mentioning

confidence: 99%

Air quality over Portugal in 2020

Monteiro

Ferreira

Ribeiro

et al. 2015

Atmospheric Pollution Research

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This works intends to evaluate the impacts of the national emission ceilings (NEC) reduction scenarios on the air quality in Portugal, verifying the fulfillment of the air quality thresholds for 2020. The air quality numerical modeling system WRF-EURAD was applied to this 2020 future scenario and results were compared to the present situationyear 2012. This modeling system was already evaluated for Portugal domain in previous studies, by comparison with measured air quality data, and showed reasonable skills for all the pollutants. This system was applied over the Continental domain of Portugal, using nesting approach, with a horizontal resolution of 5x5 km 2 , for both scenarios conditions (2012 and 2020) considering the respective emissions data and assuming the 2012 meteorological conditions. The results point towards an improvement of the air quality over Continental Portugal, in particular for particulate matter (in the urban areas of Lisbon and Porto) and SO2 (near specific industrial sources) but do not solve the non-compliance status regarding the O3 threshold value for protection of human health. These results strengthen the importance of including the NEC emission scenarios in the air quality national strategy, but additional mitigation actions need to be designed, with focus on ozone and its precursors, at local and regional scale.

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Bias Correction Techniques to Improve Air Quality Ensemble Predictions: Focus on O3 and PM Over Portugal

Cited by 29 publications

References 29 publications

Air quality plan for ozone: an urgent need for North Portugal

Air quality plan for ozone: an urgent need for North Portugal

A regional air quality forecasting system over Europe: the MACC-II daily ensemble production

Air quality over Portugal in 2020

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