Near-road air quality modelling that incorporates input variability and model uncertainty

Abstract. The multimodel ensemble exercise performed within the HTAP project context (Fiore et al., 2009) is used here as an example of how a pre-inspection, diagnosis and selection of an ensemble, can produce more reliable results. The procedure is contrasted with the often-used practice of simply averaging model simulations, assuming different models produce independent results, and using the diversity of simulation as an illusory estimate of model uncertainty. It is further and more importantly demonstrated how conclusions can drastically change when future emission scenarios are analysed using an un-inspected ensemble. The HTAP multimodel ensemble analysis is only taken as an example of a widespread and common practice in air quality modelling.

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Feature and Language Selection in Temporal Symbolic Regression for Interpretable Air Quality Modelling

Algorithms ◽

10.3390/a14030076 ◽

2021 ◽

Vol 14 (3) ◽

pp. 76

Author(s):

Estrella Lucena-Sánchez ◽

Guido Sciavicco ◽

Ionel Eduard Stan

Keyword(s):

Air Quality ◽

Fundamental Problem ◽

Multivariate Time Series ◽

Quality Data ◽

Data Sets ◽

Air Quality Modelling ◽

Regression Problem ◽

Car Traffic ◽

Pollutant Concentrations ◽

Language Selection

Air quality modelling that relates meteorological, car traffic, and pollution data is a fundamental problem, approached in several different ways in the recent literature. In particular, a set of such data sampled at a specific location and during a specific period of time can be seen as a multivariate time series, and modelling the values of the pollutant concentrations can be seen as a multivariate temporal regression problem. In this paper, we propose a new method for symbolic multivariate temporal regression, and we apply it to several data sets that contain real air quality data from the city of Wrocław (Poland). Our experiments show that our approach is superior to classical, especially symbolic, ones, both in statistical performances and the interpretability of the results.

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Sensitivity of air quality modelling to different emission inventories: a case study over Europe

Atmospheric Environment X ◽

10.1016/j.aeaoa.2021.100111 ◽

2021 ◽

pp. 100111

Author(s):

Philippe Thunis ◽

Monica Crippa ◽

Cornelis Cuvelier ◽

Diego Guizzardi ◽

Alexander de Meij ◽

...

Keyword(s):

Air Quality ◽

Emission Inventories ◽

Air Quality Modelling

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TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-10963-2014 ◽

2014 ◽

Vol 14 (20) ◽

pp. 10963-10976 ◽

Cited By ~ 200

Author(s):

J. J. P. Kuenen ◽

A. J. H. Visschedijk ◽

M. Jozwicka ◽

H. A. C. Denier van der Gon

Keyword(s):

Particulate Matter ◽

Air Quality ◽

High Resolution ◽

Emission Inventory ◽

Point Sources ◽

Air Quality Modelling ◽

Emission Data ◽

Data Set ◽

Spatially Distributed ◽

Reported Data

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these "official" emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7 × 7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution maps.

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Evaluation of Regional Emission Control Based in Photochemical Air Quality Modelling

Advanced Air Pollution ◽

10.5772/17536 ◽

2011 ◽

Author(s):

Angel Rodriguez ◽

Santiago Saavedra ◽

Maria Dios ◽

Carmen Torres ◽

Jose A. ◽

...

Keyword(s):

Air Quality ◽

Emission Control ◽

Air Quality Modelling

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Influence of different complexity levels of road traffic models on air quality modelling at street scale

Air Quality Atmosphere & Health ◽

10.1007/s11869-018-0621-1 ◽

2018 ◽

Vol 11 (10) ◽

pp. 1217-1232 ◽

Cited By ~ 9

Author(s):

Bruno Vicente ◽

Sandra Rafael ◽

Vera Rodrigues ◽

Hélder Relvas ◽

Mariana Vilaça ◽

...

Keyword(s):

Air Quality ◽

Road Traffic ◽

Air Quality Modelling ◽

Traffic Models

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Aerosols in the CALIOPE air quality modelling system: validation and analysis of PM levels, optical depths and chemical composition over Europe

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-20575-2011 ◽

2011 ◽

Vol 11 (7) ◽

pp. 20575-20629

Author(s):

S. Basart ◽

M. T. Pay ◽

O. Jorba ◽

C. Pérez ◽

P. Jiménez-Guerrero ◽

...

Keyword(s):

Air Quality ◽

Chemical Composition ◽

Air Quality Modelling ◽

Po Valley ◽

Aerosol Mass ◽

Forecasting System ◽

Bulk Parameters ◽

Quality Threshold ◽

Daily Pm10 ◽

Modelling System

Abstract. The CALIOPE high-resolution air quality modelling system is developed and applied to Europe (12 km × 12 km, 1 h). The modelled daily to seasonal aerosol variability over Europe in 2004 have been evaluated and analysed. The aerosols are estimated from two models, CMAQv4.5 (AERO4) and BSC-DREAM8b. CMAQv4.5 calculates biogenic, anthropogenic and sea salt aerosol and BSC-DREAM8b provides the natural mineral dust contribution from North African deserts. For the evaluation, we use daily PM10/PM2.5 and chemical composition data from 54 stations of the EMEP/CREATE network and coarse and fine aerosol optical depth (AOD) data from 35 stations of the AERONET sun photometer network. The model achieves daily PM10 and PM2.5 correlations of 0.57 and 0.47, respectively, and total, coarse and fine AOD correlations of 0.51, 0.63, and 0.53, respectively. The higher correlations of the PM10 and the coarse mode AOD are largely due to the accurate representation of the African dust influence in the forecasting system. Overall PM and AOD levels are underestimated. The evaluation of the chemical composition highlights underestimations of the modelled fine fractions particularly for carbonaceous matter (EC and OC) and secondary inorganic aerosols (SIA; i.e. nitrates, sulphates and ammonium). The scores of the bulk parameters are significantly improved after applying a simple model bias correction based on the chemical composition observations. SIA are dominant in the fine fractions representing up to 80 % of the aerosol budget in latitudes beyond 40° N. The highest aerosol concentrations are found over the industrialized and populated areas of the Po Valley and the Benelux regions. High values in southern Europe are linked to the transport of coarse particles from the Sahara desert which contributes up to 40 % of the total aerosol mass. Close to the surface, maxima dust seasonal concentrations (>30 μg m–3) are found between spring and early autumn. We estimate that desert dust causes daily exceedances of the PM10 European air quality threshold (50 μg m–3) in large areas south of 45° N reaching up to more than 75 days per year in the southernmost regions.

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