Modelling street level PM<sub>10</sub> concentrations across Europe: source apportionment and possible futures

Abstract

Abstract. Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM 10 (PM with aerodynamic diameter < 10 µm) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80 % of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period [2000][2001][2002][2003][2004][2005][2006][2007][2008] to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM 10 across Europe. Furthermore, we analyse the predicted evolution of PM 10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM 10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM 10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Modelling PM2.5 impact indicators in Europe: Health effects and legal compliance

“…The methodology is described in detail in Kiesewetter et al (2015) and will only be repeated briefly here.…”

“…The urban increment is derived from a full year simulation of the CHIMERE CTM (Menut et al, 2013) run at a resolution of 0.125 Â 0.0625 or roughly 7 Â 7 km 2 . Both EMEP and CHIMERE models used the same emission gridding by country and SNAP sector on the 7 Â 7 km 2 grid, as described by Kiesewetter et al (2014Kiesewetter et al ( , 2015.…”

“…Starting from the modelled fields at 0.5 Â 0.25 , a downscaling scheme is applied which increases the resolution by a factor of 16, essentially based on a redistribution of primary PM concentrations according to the primary PM emission densities from low-level sources (transport and domestic sectors), using a full year simulation of the CHIMERE CTM with the same emission gridding as used in the transfer coefficient calculations. A detailed description is given by Kiesewetter et al (2015).…”

Source apportionment and sensitivity analysis: two methodologies with two different purposes

“…On the other hand, sensitivity analysis is often used as an approach to derive source contributions, e.g. SHERPA (Thunis et al, 2016), FASST (Crippa et al, 2017) and GAINS (Kiesewetter et al, 2015). The main objective of this work is to review the existing methodologies, identify key differences and stress their implicit limitations.…”

Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning

“…Air masses from continental eastern Europe tend to transport higher amounts of particles, whereas western, more maritime air tends to be cleaner due to precipitation along the trajectories of air masses. Source regions of PM10 include industrial and residential areas in Poland and the Czech Republic with heavy industries or extensive usage of solid fuels for residential heating (Beloconi et al, 2018;Kiesewetter et al, 2015;Reizer & Juda-Rezler, 2016;van Pinxteren et al, 2019). Results by Grange et al (2018) also show increased values of PM10 for northern and northeastern wind directions, although to a lesser extent.…”