Prediction of source contributions to urban background PM10 concentrations in European cities: a case study for an episode in December 2016 using EMEP/MSC-W rv4.15 – Part 2: The city contribution

Abstract

Abstract. Despite the progress made in the latest decades, air pollution is still the\nprimary environmental cause of premature death in Europe. The urban\npopulation risks more likely to suffer to pollution related to high\nconcentrations of air pollutants, such as in particulate matter smaller than\n10\u2009µm (PM10). Since the composition of these particulates varies\nwith space and time, the understanding of the origin is essential to\ndetermine the most efficient control strategies. A source contribution calculation allows us to provide such information and\nthus to determine the geographical location of the sources (e.g. city or\ncountry) responsible for the air pollution episodes. In this study, the\ncalculations provided by the regional European Monitoring and Evaluation\nProgramme/Meteorological Synthesizing Centre – West (EMEP/MSC-W) rv4.15 model in a forecast\nmode, with a 0.25∘ longitude × 0.125∘ latitude\nresolution, and based on a scenario approach, have been explored. To do so,\nthe work has focused on event occurring between 1 and 9\xa0December 2016.\nThis source contribution calculation aims at quantifying over 34 European\ncities, the “city” contribution of these PM10, i.e. from the city\nitself, on an hourly basis. Since the methodology used in the model is based\non reduced anthropogenic emissions, compared to a reference run, the choice\nof the percentage in the reductions has been tested by using three different\nvalues (5\u2009%, 15\u2009%, and 50\u2009%). The definition of the “city”\ncontribution, and thus the definition of the area defining the cities is\nalso an important parameter. The impact of the definition of these urban\nareas, for the studied cities, was investigated (i.e. one model grid cell, nine\ngrid cells and the grid cells covering the definition given by the global\nadministrative area – GADM). Using a 15\u2009% reduction in the emission and larger cities for\nour source contribution calculation (e.g. nine grid cells and GADM) helps to\nreduce the non-linearity in the concentration changes. This non-linearity is\nobserved in the mismatch between the total concentration and the sum of the\nconcentrations from different calculated sources. When this non-linearity is\nobserved, it impacts the NO3-, NH4+, and H2O\nconcentrations. However, the mean non-linearity represents only less than\n2\u2009% of the total modelled PM10 calculated by the system. During the studied episode, it was found that 20\u2009% of the surface\npredicted PM10 had been from the “city”, essentially composed of\nprimary components. In total, 60\u2009% of the hourly PM10 concentrations predicted\nby the model came from the countries in the regional domain, and they were\nessentially composed of NO3- (by ∼\u200935 \u2009%). The two\nother secondary inorganic aerosols are also important components of this\n“rest of Europe” contribution, since SO42- and NH4+\nrepresent together almost 30\u2009% of this contribution. The rest of the\nPM10 was mainly due to natural sources. It was also shown that the\ncentral European cities were mainly impacted by the surrounding countries\nwhile the cities located a bit away from the rest of the other European\ncountries (e.g. Oslo and Lisbon) had larger “city” contributions. The\nusefulness of the forecasting tool has also been illustrated with an example\nin Paris, since the system has been able to predict the primary sources of a\nlocal polluted event on 1–2\xa0December 2016, as documented by local\nauthorities.\n