Abstract

Cooking activities are a source of urban air pollution that has been often ignored. The corresponding particulate matter (PM) emissions are not included or are seriously underestimated in urban emission inventories. However, several field studies suggest that cooking organic aerosol (COA) can be an important component of the organic PM in urban areas. In this study we propose and evaluate a methodology for the simulation of the COA concentration and its variability in space and time in an urban area. The city of Patras, the third biggest in Greece, is used for this first application during a typical late summer period.The spatial distribution of COA emissions was based on the exact location of restaurants and grills, while the emission rates on the per person meat consumption in Greece. We estimated COA emissions of 0.6 g d−1 per person that corresponds to 150 kg d−1 for Patras. The temporal distribution of COA emissions was based on the known cooking times and the results of past field studies in the area. We estimated that half of the daily COA is emitted during dinner time (21:00–0:00 LT), while approximately 25% during lunch time (13:00–16:00 LT). The COA is simulated using the Volatility Basis Set approach and is treated as semivolatile and reactive. Its volatility distribution is based on laboratory measurements of COA from meat grilling.The chemical transport model PMCAMx predicts that the COA concentration reaches values up to 15 μg m−3 during the nights of the simulated summertime period in an area with high restaurant density. The average predicted COA concentration is around 1.2 μg m−3 in the center and 0.1–0.2 μg m−3 in the suburbs of the city. COA has a distinct daily profile that peaks during lunch (13:00–15:00 LT) and dinner (21:00–23:00 LT) periods. The local production of secondary COA is predicted to be slow and it represents just a few percent of the total COA. The model reproduces well the average PM2.5 concentrations at the outskirts of Patras and its overall performance for hourly PM2.5 values is rated as good. A 50% uncertainty of the reported COA emissions is estimated based on the results of the sensitivity tests and the observations in the city core. The emissions can be further constrained and the corresponding uncertainty can be further reduced with measurements focusing on COA and not on total PM2.5 as was the case in this study. These should take place in different areas of the city, selected based on the model predictions, to also improve our estimates of the spatial distribution of the emissions.

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