Determinants of spatial variability of air pollutant concentrations in a street canyon network measured using a mobile laboratory and a drone.

Urban air pollutant concentrations are highly variable both in space and time. In order to understand these variabilities high-resolution measurements of air pollutants are needed. Here we present results of a mobile laboratory and a drone measurements made within a street-canyon network in Helsinki, Finland, in summer and winter 2017. The mobile laboratory measured the total number concentration (N) and lung-deposited surface area (LDSA) of aerosol particles, and the concentrations of black carbon, nitric oxide (NOx) and ozone (O3). The drone measured the vertical profile of LDSA. The main aims were to examine the spatial variability of air pollutants in a wide street canyon and its immediate surroundings, and find the controlling environmental variables for the observed variability's. The highest concentrations with the most temporal variability were measured at the main street canyon when the mobile laboratory was moving with the traffic fleet for all air pollutants except O3. The street canyon concentration levels were more affected by traffic rates whereas on surrounding areas, meteorological conditions dominated. Both the mean flow and turbulence were important, the latter particularly for smaller aerosol particles through LDSA and N. The formation of concentration hotspots in the street network were mostly controlled by mechanical processes but in winter thermal processes became also important for aerosol particles. LDSA showed large variability in the profile shape, and surface and background concentrations. The expected exponential decay functions worked better in well-mixed conditions in summer compared to winter. We derived equation for the vertical decay which was mostly controlled by the air temperature. Mean wind dominated the profile shape over both thermal and mechanical turbulence. This study is among the first experimental studies to demonstrate the importance of high-resolution measurements in understanding urban pollutant variability in detail.

An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation.

An operational urban air quality modelling system ENFUSER is presented with an evaluation against measured data. ENFUSER combines several dispersion modelling approaches, uses data assimilation, and continuously extracts information from online, global open-access sources. The modelling area is described with a combination of geographic datasets. These GIS datasets are globally available with open access, and therefore the model can be applied worldwide. Urban scale dispersion is addressed with a combination of Gaussian puff and Gaussian plume modelling, and long-range transport of pollutants is accounted for via a separate regional model. The presented data assimilation method, which supports the use of AQ sensors and incorporates a longer-term learning mechanism, adjusts emission factors and the regional background values on an hourly basis. The model can be used with reasonable accuracy also in urban areas, for which detailed emissions inventories would not be available, due to the data assimilation capabilities.

Is reducing new particle formation a plausible solution to mitigate particulate air pollution in Beijing and other Chinese megacities?

Atmospheric gas-to-particle conversion is a crucial or even dominant contributor to haze formation in Chinese megacities in terms of aerosol number, surface area and mass. Based on our comprehensive observations in Beijing during 15 January 2018-31 March 2019, we are able to show that 80-90% of the aerosol mass (PM2.5) was formed via atmospheric reactions during the haze days and over 65% of the number concentration of haze particles resulted from new particle formation (NPF). Furthermore, the haze formation was faster when the subsequent growth of newly formed particles was enhanced. Our findings suggest that in practice almost all present-day haze episodes originate from NPF, mainly since the direct emission of primary particles in Beijing has considerably decreased during recent years. We also show that reducing the subsequent growth rate of freshly formed particles by a factor of 3-5 would delay the buildup of haze episodes by 1-3 days. Actually, this delay would decrease the length of each haze episode, so that the number of annual haze days could be approximately halved. Such improvement in air quality can be achieved with targeted reduction of gas-phase precursors for NPF, mainly dimethyl amine and ammonia, and further reductions of SO2 emissions. Furthermore, reduction of anthropogenic organic and inorganic precursor emissions would slow down the growth rate of newly-formed particles and consequently reduce the haze formation.